Triple
T4745854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Demand |
E105358
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Office |
E413052
|
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: Office | Statement: [Thomas Demand, notableWork, Office]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Office Context triple: [Thomas Demand, notableWork, Office]
-
A.
Home Office
The Home Office is a major UK government department responsible for immigration, security, and law and order, including policing and counter-terrorism.
-
B.
Office Space
Office Space is a 1999 cult-classic workplace comedy film that satirizes corporate office culture and the frustrations of white-collar employees.
-
C.
"Office"
chosen
"Office" is a 2015 Hong Kong musical comedy-drama film directed by Johnnie To, adapted from Sylvia Chang’s stage play and set in a high-rise corporation to satirize modern office politics and capitalism.
-
D.
Office Mobile
Office Mobile is a mobile-optimized version of Microsoft Office that lets users view, edit, and create Office documents on smartphones and other portable devices.
-
E.
One Office
One Office is an integrated organizational model used in the UN’s “Delivering as One” approach to streamline internal operations and support more coherent, efficient country-level work.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd43ef87a48190a5bc3600711aa032 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64ab946481909eccdb3e8c5d1f6a |
completed | March 20, 2026, 3:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be3a40bee88190ae97f6d409b51e96 |
completed | March 21, 2026, 6:27 a.m. |
Created at: March 20, 2026, 1:20 p.m.