Triple
T1703409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman aediles |
E36815
|
entity |
| Predicate | usedOfficeFor |
P32438
|
FINISHED |
| Object | gaining popularity through lavish games |
—
|
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: gaining popularity through lavish games | Statement: [Roman aediles, usedOfficeFor, gaining popularity through lavish games]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedOfficeFor Context triple: [Roman aediles, usedOfficeFor, gaining popularity through lavish games]
-
A.
usedByOffice
Indicates that something is utilized, operated, or employed by an office or office-related entity.
-
B.
worksWithOffice
Indicates that an entity collaborates or is professionally associated with a particular office or office-based organization.
-
C.
officeIsIn
Indicates that one office is located within or inside another specified place or building.
-
D.
office
Indicates that an entity holds or occupies an official position, role, or post within an organization or institution.
-
E.
includedOffice
Indicates that one office is contained within, or forms part of, another office or organizational unit.
- 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_69a88617439c819094ffb5d16a0f6307 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab75ad24408190814069e6e3ef9e59 |
completed | March 7, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69aa61bad17c8190861b92cfb423f68f |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab75ac1408819086b22b3cd0672a79 |
completed | March 7, 2026, 12:47 a.m. |
Created at: March 4, 2026, 7:30 p.m.