Triple
T5808833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tasman District |
E128815
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Tim King
Tim King is a New Zealand local-body politician who serves as the mayor of the Tasman District.
|
E547558
|
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: Tim King | Statement: [Tasman District, hasMayor, Tim King]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tim King Context triple: [Tasman District, hasMayor, Tim King]
-
A.
Jeff King
Jeff King is a television producer and writer known for his work on various drama series.
-
B.
Alan King
Alan King was an American comedian and character actor known for his sharp observational humor and frequent film and television roles from the 1950s through the 1990s.
-
C.
Mike King
Mike King is an American professional baseball pitcher who played college baseball at Boston College before reaching Major League Baseball.
-
D.
Ed King
Ed King was an American rock guitarist and songwriter best known as a member of Lynyrd Skynyrd, co-writing hits like "Sweet Home Alabama."
-
E.
Jacob King
Jacob King is the determined and enigmatic South African protagonist of the action-thriller film "Message from the King," who travels to Los Angeles to uncover the truth behind his sister’s disappearance and seek revenge.
- 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: Tim King Triple: [Tasman District, hasMayor, Tim King]
Generated description
Tim King is a New Zealand local-body politician who serves as the mayor of the Tasman District.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tim King Target entity description: Tim King is a New Zealand local-body politician who serves as the mayor of the Tasman District.
-
A.
Jeff King
Jeff King is a television producer and writer known for his work on various drama series.
-
B.
Alan King
Alan King was an American comedian and character actor known for his sharp observational humor and frequent film and television roles from the 1950s through the 1990s.
-
C.
Mike King
Mike King is an American professional baseball pitcher who played college baseball at Boston College before reaching Major League Baseball.
-
D.
Ed King
Ed King was an American rock guitarist and songwriter best known as a member of Lynyrd Skynyrd, co-writing hits like "Sweet Home Alabama."
-
E.
Jacob King
Jacob King is the determined and enigmatic South African protagonist of the action-thriller film "Message from the King," who travels to Los Angeles to uncover the truth behind his sister’s disappearance and seek revenge.
- 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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b1867a481909a7ea3331dbb04ce |
completed | March 22, 2026, 5:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0983ded9c8190b37372627c1e3a50 |
completed | March 23, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69c0990bf38081908c09c5dfe660c35b |
completed | March 23, 2026, 1:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c099bd26fc8190a58bf483a6d4cbca |
completed | March 23, 2026, 1:39 a.m. |
Created at: March 22, 2026, 3:52 p.m.