Triple
T37576321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asian Jim |
E934829
|
entity |
| Predicate | hasColleagueInScene |
P120814
|
FINISHED |
| Object | Pam Beesly |
E223028
|
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: Pam Beesly | Statement: [Asian Jim, hasColleagueInScene, Pam Beesly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColleagueInScene Context triple: [Asian Jim, hasColleagueInScene, Pam Beesly]
-
A.
hasCompanionColleague
Indicates that one entity has another entity as a colleague who also serves as a companion or close associate.
-
B.
hasColleagues
chosen
Indicates that one entity works alongside another in a professional or organizational context as colleagues.
-
C.
hasColleagueOffice
Indicates that one entity has an office that is shared with or located near the office of another colleague entity.
-
D.
hasSiblingCoStars
Indicates that two or more entities have appeared together as co-stars and are siblings in relation to each other.
-
E.
hasCollaborationIn
Indicates that two or more entities work together or jointly participate in a specific project, context, or domain.
- F. None of above.
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_69f76ecd99148190be327e391a70f5b6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40afd8a9dc8190a8971d8c96da5377 |
completed | June 28, 2026, 5:23 a.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:17 p.m.