Triple
T1765337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palais du Gouverneur général de l’Indochine |
E38748
|
entity |
| Predicate | endUseTime |
P6544
|
FINISHED |
| Object | mid 20th century |
—
|
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: mid 20th century | Statement: [Palais du Gouverneur général de l’Indochine, endUseTime, mid 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: endUseTime Context triple: [Palais du Gouverneur général de l’Indochine, endUseTime, mid 20th century]
-
A.
usedUntil
chosen
Indicates that something remained in use or operation up to a specified time or event, after which it was no longer used.
-
B.
durationOfUse
Indicates the length of time for which something is used or remains in use.
-
C.
evaDuration
Indicates the length of time that an extravehicular activity (EVA) lasts or is scheduled to last.
-
D.
spentTimeIn
Indicates that an entity has spent a certain amount or period of time in a particular place or context.
-
E.
timeToComplete
Indicates the duration required for an entity or process to be fully completed.
- F. None of above.
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_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab39fc2c448190bfaf1ee8d474632a |
completed | March 6, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69aa61cbb1288190a7ba38b61905f578 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.