Triple
T30179879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hittite sack of Babylon |
E767170
|
entity |
| Predicate | impactOnBabylon |
P137129
|
FINISHED |
| Object | destruction and looting of the city |
—
|
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: destruction and looting of the city | Statement: [Hittite sack of Babylon, impactOnBabylon, destruction and looting of the city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnBabylon Context triple: [Hittite sack of Babylon, impactOnBabylon, destruction and looting of the city]
-
A.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
B.
impactStatus
chosen
Indicates the current state or condition of how something has affected or influenced a target.
-
C.
impactEvent
Indicates that one entity physically strikes or collides with another, producing a resulting effect or change.
-
D.
impactTower
Indicates that one entity exerts a significant force or collision upon a tower-like structure, affecting its state or stability.
-
E.
impactScope
Indicates the extent or range within which an action, event, or entity produces effects or consequences.
- 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_69f2247ba20c81909d34f2bfed706e1e |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f71996e1a48190ac59a1d66d7c44e8 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
Created at: April 29, 2026, 7:26 p.m.