Triple
T28140558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moctesuma Esparza |
E714328
|
entity |
| Predicate | produced |
P490
|
FINISHED |
| Object |
Price of Glory
Price of Glory is a 2000 sports drama film about a former boxer who tries to achieve success through his three sons in the boxing ring.
|
E1805105
|
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: Price of Glory | Statement: [Moctesuma Esparza, produced, Price of Glory]
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: Price of Glory Triple: [Moctesuma Esparza, produced, Price of Glory]
Generated description
Price of Glory is a 2000 sports drama film about a former boxer who tries to achieve success through his three sons in the boxing ring.
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_69efd6af156c81908f50c2cd7db0e1ef |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f64133fc4081908f9d682dcfdbd517 |
completed | May 2, 2026, 6:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a15d7a249808190a822fb949af996ea |
completed | May 26, 2026, 5:25 p.m. |
| NEDg | Description generation | batch_6a15dad9fac881908a639795ac0a908b |
completed | May 26, 2026, 5:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a15db82ef1481908402a27126482289 |
completed | May 26, 2026, 5:42 p.m. |
Created at: April 27, 2026, 9:53 p.m.