Triple
T8259410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Odesa Opera and Ballet Theater |
E193154
|
entity |
| Predicate | firstBuildingDestroyedByFire |
P81247
|
FINISHED |
| Object | 1873 |
—
|
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: 1873 | Statement: [Odesa Opera and Ballet Theater, firstBuildingDestroyedByFire, 1873]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstBuildingDestroyedByFire Context triple: [Odesa Opera and Ballet Theater, firstBuildingDestroyedByFire, 1873]
-
A.
originalBuildingDestroyedBy
Indicates that the original building was destroyed as a result of the actions or effects of the specified agent or cause.
-
B.
secondBuildingDestroyedBy
Indicates that the second building in a specified context is the one that was destroyed by a particular agent or event.
-
C.
significantBuildingFire
Indicates a relationship where a building is involved in a fire event of notable size, intensity, or impact.
-
D.
houseBurned
Indicates that a house has been destroyed or significantly damaged by fire.
-
E.
firstPalaceDestroyedIn
Indicates that the first palace associated with an entity was destroyed in a specified event, time, or place.
- 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_69ca82dfad9c8190b8cd18fb89f50f40 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78fe5e2c819080741ea24bae0807 |
completed | March 31, 2026, 7:34 a.m. |
| PD | Predicate disambiguation | batch_69cb36b6d5548190b665a6cce14c69f7 |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb44d1caa881909069fa925a91316b |
completed | March 31, 2026, 3:51 a.m. |
Created at: March 30, 2026, 5:49 p.m.