Triple
T35177379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimmerioi |
E1015745
|
entity |
| Predicate | associatedWithCityDestruction |
P206857
|
FINISHED |
| Object | Phrygian kingdom |
E1843859
|
NE 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: Phrygian kingdom | Statement: [Kimmerioi, associatedWithCityDestruction, Phrygian kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCityDestruction Context triple: [Kimmerioi, associatedWithCityDestruction, Phrygian kingdom]
-
A.
mainCityDestroyed
Indicates that the primary or central city associated with an entity has been destroyed.
-
B.
destroyedCity
Indicates that an entity has caused the complete or near-complete destruction of a city.
-
C.
sufferedDestructionIn
Indicates that an entity experienced damage, ruin, or devastation during or as part of a specified event or period.
-
D.
percentageCityDestroyed
Indicates the proportion of a city that has been destroyed, typically expressed as a percentage of its total area or infrastructure.
-
E.
sufferedDestructionOf
Indicates that one entity experienced damage, ruin, or loss as a result of the destruction of another entity.
- F. None of above. chosen
Provenance (5 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_69f76ddcc108819097f96853b7ed9ef4 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a37fb1757bc81909365f66fb30f2380 |
completed | June 21, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:02 p.m.