Triple
T11361114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Punta Raisi |
E269086
|
entity |
| Predicate | distanceToPalermoApprox |
P98912
|
FINISHED |
| Object | about 35 kilometres northwest of Palermo |
—
|
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: about 35 kilometres northwest of Palermo | Statement: [Punta Raisi, distanceToPalermoApprox, about 35 kilometres northwest of Palermo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPalermoApprox Context triple: [Punta Raisi, distanceToPalermoApprox, about 35 kilometres northwest of Palermo]
-
A.
distanceFromNaples
Indicates the spatial distance between a given entity and the city of Naples.
-
B.
distanceToPadua
Indicates the measured distance between a given entity’s location and the city of Padua.
-
C.
distanceToRome
Indicates the spatial distance between a given entity and the location of Rome.
-
D.
distanceToBrindisi
Indicates the measured or specified distance between a given entity or location and the city of Brindisi.
-
E.
distanceToSavona_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Savona.
- F. None of above. chosen
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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d800160a1c81909d115bf89fe54a49 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e7022d508190996f9be0847c2b41 |
completed | April 9, 2026, 5:50 p.m. |
| PDg | Predicate description generation | batch_69d80010712c819089ea2e31e664abe1 |
completed | April 9, 2026, 7:37 p.m. |
Created at: April 8, 2026, 9:33 p.m.