Triple
T34900059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Keenan |
E1006557
|
entity |
| Predicate | roleAtInXileEntertainment |
P182449
|
FINISHED |
| Object | developer |
—
|
LITERAL 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: developer | Statement: [Chris Keenan, roleAtInXileEntertainment, developer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleAtInXileEntertainment Context triple: [Chris Keenan, roleAtInXileEntertainment, developer]
-
A.
roleInTheatreEcosystem
Indicates the specific function, responsibility, or position an entity holds within the interconnected system of theatre production, distribution, and audience engagement.
-
B.
roleInLanternEntertainment
Indicates that an entity holds or held a specific role or position within Lantern Entertainment.
-
C.
roleInFilmEcosystem
Indicates the specific function or position an entity holds within the broader network of activities, stakeholders, and processes that make up the film ecosystem.
-
D.
playsInRole
Indicates that an entity performs or appears in a specific role within a production, event, or context.
-
E.
entertainmentRole
Indicates that an entity holds a specific function or position within an entertainment context (such as a role in a performance, production, or media work).
- F. None of above. chosen
Provenance (4 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_69f76dbfe5788190ad8b64f241f470c8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78d7211a48190bfb59c406f0bf12f |
completed | May 3, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78c6014e08190864785a4fe3e8e73 |
completed | May 3, 2026, 5:56 p.m. |
Created at: May 3, 2026, 4 p.m.