Triple
T3287017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charly Baltimore |
E69005
|
entity |
| Predicate | enemyOf |
P437
|
FINISHED |
| Object |
Timothy
Timothy is a character known primarily as the adversary of Charly Baltimore in the action thriller film "The Long Kiss Goodnight."
|
E346059
|
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: Timothy | Statement: [Charly Baltimore, enemyOf, Timothy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Timothy Context triple: [Charly Baltimore, enemyOf, Timothy]
-
A.
Timothy
Timothy is the given first name of Sir Tim Berners-Lee, the British computer scientist who invented the World Wide Web.
-
B.
Timothy
Timothy is a prominent early Christian companion and protégé of the Apostle Paul, known from the New Testament for his missionary work and pastoral leadership.
-
C.
Tobias
Tobias is the full given name of Toby Ziegler, the fictional White House Communications Director from the television series "The West Wing."
-
D.
Tobias
Tobias was a Native American man from the 17th-century Wampanoag community, known primarily through his familial connection to the Sakonnet leader Awashonks.
-
E.
Tobias
Tobias is the virtuous young protagonist of the biblical Book of Tobit, known for his journey with the angel Raphael and the healing of his father’s blindness.
- 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: Timothy Triple: [Charly Baltimore, enemyOf, Timothy]
Generated description
Timothy is a character known primarily as the adversary of Charly Baltimore in the action thriller film "The Long Kiss Goodnight."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Timothy Target entity description: Timothy is a character known primarily as the adversary of Charly Baltimore in the action thriller film "The Long Kiss Goodnight."
-
A.
Timothy
Timothy is the given first name of Sir Tim Berners-Lee, the British computer scientist who invented the World Wide Web.
-
B.
Timothy
Timothy is a prominent early Christian companion and protégé of the Apostle Paul, known from the New Testament for his missionary work and pastoral leadership.
-
C.
Tobias
Tobias is the full given name of Toby Ziegler, the fictional White House Communications Director from the television series "The West Wing."
-
D.
Tobias
Tobias was a Native American man from the 17th-century Wampanoag community, known primarily through his familial connection to the Sakonnet leader Awashonks.
-
E.
Tobias
Tobias is the virtuous young protagonist of the biblical Book of Tobit, known for his journey with the angel Raphael and the healing of his father’s blindness.
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb05779d08190a5517951e71b1380 |
completed | March 8, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3cd5f508190ac5abc2dcdf0957d |
completed | March 12, 2026, 5:11 p.m. |
| NEDg | Description generation | batch_69b2fa5bd7f88190b24377e38f49371b |
completed | March 12, 2026, 5:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b309509ab0819083ed192402866470 |
completed | March 12, 2026, 6:43 p.m. |
Created at: March 8, 2026, 3:10 p.m.