Triple
T30968552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tell as-Senkereh |
E789026
|
entity |
| Predicate | associatedWithAncientCityState |
P107813
|
FINISHED |
| Object | Larsa |
E222443
|
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: Larsa | Statement: [Tell as-Senkereh, associatedWithAncientCityState, Larsa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithAncientCityState Context triple: [Tell as-Senkereh, associatedWithAncientCityState, Larsa]
-
A.
relatesToAncientCity
chosen
Indicates a relationship or connection between an entity and an ancient city, such as origin, location, influence, or relevance.
-
B.
hasAncientCityState
Indicates that one entity possesses, contains, or is associated with an ancient city-state as part of its historical or geographical context.
-
C.
associatedWithAncientEmpire
Indicates that one entity has a historical, cultural, political, or geographic connection or affiliation with an ancient empire.
-
D.
ancientCity
Indicates that the subject is a historically old or long-established city, typically originating from ancient times.
-
E.
hasNearbyAncientCity
Indicates that one entity is located close to another entity that is classified as an ancient city.
- F. None of above.
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_69f224c3a6b48190951add9b7b7f0271 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a292afe74e0819090c7a08fa589573e |
completed | June 10, 2026, 9:14 a.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:54 p.m.