Triple
T18905780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal-Mogul |
E462457
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object |
Beru
Beru is an automotive brand known for producing ignition technology and related components such as spark plugs and glow plugs.
|
E1348857
|
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: Beru | Statement: [Federal-Mogul, brand, Beru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beru Context triple: [Federal-Mogul, brand, Beru]
-
A.
Beru
Beru is a low-lying coral atoll in the southern Gilbert Islands of Kiribati, known for its traditional villages, lagoon, and vulnerability to sea-level rise.
-
B.
Beru Lars
Beru Lars is Luke Skywalker’s kind and protective aunt on Tatooine, who helps raise him on the Lars moisture farm in the Star Wars saga.
-
C.
Gloria Hutt
Gloria Hutt is a Chilean politician known for her leadership roles in public office and her prominent participation in the center-right political party Evópoli.
-
D.
Rose Tico
Rose Tico is a Resistance mechanic-turned-hero in the Star Wars sequel trilogy who fights alongside Finn against the First Order.
-
E.
Tani Rey
Tani Rey is a former police academy recruit who becomes a key member of the elite task force in the rebooted television series Hawaii Five-0.
- 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: Beru Triple: [Federal-Mogul, brand, Beru]
Generated description
Beru is an automotive brand known for producing ignition technology and related components such as spark plugs and glow plugs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Beru Target entity description: Beru is an automotive brand known for producing ignition technology and related components such as spark plugs and glow plugs.
-
A.
Beru
Beru is a low-lying coral atoll in the southern Gilbert Islands of Kiribati, known for its traditional villages, lagoon, and vulnerability to sea-level rise.
-
B.
Beru Lars
Beru Lars is Luke Skywalker’s kind and protective aunt on Tatooine, who helps raise him on the Lars moisture farm in the Star Wars saga.
-
C.
Gloria Hutt
Gloria Hutt is a Chilean politician known for her leadership roles in public office and her prominent participation in the center-right political party Evópoli.
-
D.
Rose Tico
Rose Tico is a Resistance mechanic-turned-hero in the Star Wars sequel trilogy who fights alongside Finn against the First Order.
-
E.
Tani Rey
Tani Rey is a former police academy recruit who becomes a key member of the elite task force in the rebooted television series Hawaii Five-0.
- 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c52cc9cc8190ac489d36e51693c8 |
completed | April 20, 2026, 6:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0582bf4f9481908098c8d405225553 |
completed | May 14, 2026, 8:07 a.m. |
| NEDg | Description generation | batch_6a05899f7a008190a9b0324f403f09ac |
completed | May 14, 2026, 8:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a058a1028288190b9fddb9b6b123651 |
completed | May 14, 2026, 8:38 a.m. |
Created at: April 10, 2026, 11:58 a.m.