Triple
T31513446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terra di Lavoro |
E804002
|
entity |
| Predicate | historicalCoreCity |
P145012
|
FINISHED |
| Object | Capua |
—
|
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: Capua | Statement: [Terra di Lavoro, historicalCoreCity, Capua]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalCoreCity Context triple: [Terra di Lavoro, historicalCoreCity, Capua]
-
A.
focusCityHistory
Indicates that there is a historical or context-defining relationship between a focal city and its past events, developments, or status.
-
B.
isHistoricalCity
Indicates that a city has historical significance, typically due to its age, past events, or preserved heritage.
-
C.
capitalOrMajorCityHistorically
Indicates that a place has historically served as a capital or as a major, centrally important city for a political or cultural entity.
-
D.
hasHistoricCity
Indicates that an entity possesses, contains, or is associated with a city recognized for its historical significance.
-
E.
historicalCenterFor
chosen
Indicates that one entity has served as a central or focal place of historical significance, activity, or development for another entity.
- 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_69f348ceb0a48190ae7feca263b6296c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff46afe7e481908f2862ed11c88db2 |
completed | May 9, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69ff45e9151881909c444a655e852165 |
completed | May 9, 2026, 2:34 p.m. |
Created at: April 30, 2026, 9:51 p.m.