Triple
T38597411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Las Vegas |
E934117
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Danny McCoy
Danny McCoy is the charismatic former Marine who serves as head of security and later casino operations at the fictional Montecito Resort and Casino in the television series "Las Vegas."
|
E2276854
|
NE FINISHED |
How this triple was built (2 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: Danny McCoy | Statement: [Las Vegas, mainCharacter, Danny McCoy]
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: Danny McCoy Triple: [Las Vegas, mainCharacter, Danny McCoy]
Generated description
Danny McCoy is the charismatic former Marine who serves as head of security and later casino operations at the fictional Montecito Resort and Casino in the television series "Las Vegas."
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_69f76ecc17688190b389b693a5927501 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcd9522bd081908c55f782a5d6fcdf |
completed | May 7, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41eaa43f2481909bca0d4b04c6fbce |
completed | June 29, 2026, 3:46 a.m. |
| NEDg | Description generation | batch_6a41eb4f26e481908d2c85e0d36444e2 |
completed | June 29, 2026, 3:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a41ebd65c688190bbc848f604bd9e3c |
completed | June 29, 2026, 3:51 a.m. |
Created at: May 3, 2026, 4:32 p.m.