Triple
T1693033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chongqing |
E36590
|
entity |
| Predicate | wartimeCapitalPeriod |
P17922
|
FINISHED |
| Object | 1937–1946 |
—
|
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: 1937–1946 | Statement: [Chongqing, wartimeCapitalPeriod, 1937–1946]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wartimeCapitalPeriod Context triple: [Chongqing, wartimeCapitalPeriod, 1937–1946]
-
A.
warPeriod
Indicates a time span during which a state of war or armed conflict is ongoing between parties.
-
B.
warDamagePeriod
Indicates the time span during which damage caused by war or armed conflict occurred or was in effect.
-
C.
occupationPeriod
Indicates the time span during which an entity holds or held a particular occupation or role.
-
D.
wartimeControl
Indicates that one entity exercises authoritative command or governance over another entity specifically during a period of armed conflict or war.
-
E.
capitalDuringEra
chosen
Indicates that a city or settlement served as the capital of a political entity during a specified historical era or time period.
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf169da888190b3aa334752f1952b |
completed | March 6, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69aa61b8ce348190b46154af0b041ff0 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:29 p.m.