Triple
T31419744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bel of Palmyra |
E801495
|
entity |
| Predicate | templeDestroyedBy |
P92871
|
FINISHED |
| Object | Islamic State of Iraq and the Levant |
—
|
NE NERFINISHED |
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: Islamic State of Iraq and the Levant | Statement: [Bel of Palmyra, templeDestroyedBy, Islamic State of Iraq and the Levant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: templeDestroyedBy Context triple: [Bel of Palmyra, templeDestroyedBy, Islamic State of Iraq and the Levant]
-
A.
templeDestroyedIn
Indicates that a temple was destroyed at or during a specified time or event.
-
B.
shrineDestroyedBy
chosen
Indicates that a shrine has been ruined, demolished, or otherwise destroyed as a result of the actions of a specified agent or cause.
-
C.
firstTempleDestroyedBy
Indicates that the specified agent or force is responsible for destroying the first temple associated with the given entity.
-
D.
secondTempleDestroyedBy
Indicates that the Second Temple was destroyed by the specified agent or cause.
-
E.
statusAfterTempleDestruction
Indicates the condition or state of an entity that applies specifically after the destruction of the temple.
- 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_69f348c26f048190b4adadd71b4596c5 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a916d2e08190bafc01cba73b6469 |
completed | May 3, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69f6a7548eb48190a69b60a3c6ad53b9 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 30, 2026, 8:47 p.m.