Triple
T1324670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ligurians |
E28298
|
entity |
| Predicate | locatedInThePast |
P12102
|
FINISHED |
| Object | northwestern Italian Peninsula |
—
|
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: northwestern Italian Peninsula | Statement: [Ligurians, locatedInThePast, northwestern Italian Peninsula]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInThePast Context triple: [Ligurians, locatedInThePast, northwestern Italian Peninsula]
-
A.
locatedInOldCity
Indicates that an entity is situated within the boundaries of an old or historic part of a city.
-
B.
occurredIn
Indicates that an event or action took place within a specific location, context, or time frame.
-
C.
historicallyIn
chosen
Indicates that one entity existed, occurred, or was situated within the historical context, period, or jurisdiction associated with another entity.
-
D.
locatedAfter
Indicates that one entity is positioned later than another along a defined sequence, order, or spatial/temporal axis.
-
E.
historicallyGivenIn
Indicates that something was customarily or traditionally granted, presented, or assigned to something or someone in the past.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19e81c0819092f85201ae34422a |
completed | March 1, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69a4beedb49c8190beb5b85cdda05013 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.