Triple
T22454633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CT Corp |
E555082
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object |
Mega Corp
Mega Corp is a subsidiary company within the Indonesian conglomerate CT Corp’s diversified business portfolio.
|
E1537538
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Mega Corp | Statement: [CT Corp, hasSubsidiary, Mega Corp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mega Corp Context triple: [CT Corp, hasSubsidiary, Mega Corp]
-
A.
Big Corporation
Big Corporation is a fictional corporate entity that serves as the central focus of the narrative in "The First Time."
-
B.
Marcus Corporation
Marcus Corporation is a U.S.-based company best known for its movie theatre and hospitality businesses, including operating cinema chains and hotels.
-
C.
Mogul Corporation
Mogul Corporation was an earlier automotive parts and industrial products company that eventually evolved into or was absorbed by Federal-Mogul.
-
D.
Snow Corporation
Snow Corporation is a South Korean tech company best known for its mobile photo and video apps, including the popular selfie and augmented reality camera app SNOW.
-
E.
United Company
United Company was a prominent late 17th-century London theatre company formed by the merger of the King’s Company and the Duke’s Company, active during the Restoration period.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mega Corp Triple: [CT Corp, hasSubsidiary, Mega Corp]
Generated description
Mega Corp is a subsidiary company within the Indonesian conglomerate CT Corp’s diversified business portfolio.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mega Corp Target entity description: Mega Corp is a subsidiary company within the Indonesian conglomerate CT Corp’s diversified business portfolio.
-
A.
Big Corporation
Big Corporation is a fictional corporate entity that serves as the central focus of the narrative in "The First Time."
-
B.
Marcus Corporation
Marcus Corporation is a U.S.-based company best known for its movie theatre and hospitality businesses, including operating cinema chains and hotels.
-
C.
Mogul Corporation
Mogul Corporation was an earlier automotive parts and industrial products company that eventually evolved into or was absorbed by Federal-Mogul.
-
D.
Snow Corporation
Snow Corporation is a South Korean tech company best known for its mobile photo and video apps, including the popular selfie and augmented reality camera app SNOW.
-
E.
United Company
United Company was a prominent late 17th-century London theatre company formed by the merger of the King’s Company and the Duke’s Company, active during the Restoration period.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4e2bd4819083e5bed44e9776c6 |
completed | April 29, 2026, 1:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b0c7d6324819086dc3b07bf77c64a |
completed | May 18, 2026, 12:56 p.m. |
| NEDg | Description generation | batch_6a0b0d2ba1e08190b2ebd1ee42641fd1 |
completed | May 18, 2026, 12:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b0daf9bac819086166985458f6742 |
completed | May 18, 2026, 1:01 p.m. |
Created at: April 16, 2026, 8:48 p.m.