Triple
T27770620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montserrat massif |
E701732
|
entity |
| Predicate | approximateDistanceToBarcelona |
P74868
|
FINISHED |
| Object | about 45 km northwest |
—
|
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 45 km northwest | Statement: [Montserrat massif, approximateDistanceToBarcelona, about 45 km northwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateDistanceToBarcelona Context triple: [Montserrat massif, approximateDistanceToBarcelona, about 45 km northwest]
-
A.
distanceToBarcelonaKm
chosen
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Barcelona.
-
B.
distanceToMadrid
Indicates the physical distance between a given location or entity and the city of Madrid.
-
C.
distanceToZaragoza
Indicates the spatial distance between a given entity or location and the city of Zaragoza.
-
D.
distanceTo Palma de Mallorca (approximate km)
Indicates the approximate distance in kilometers between an entity’s location and Palma de Mallorca.
-
E.
distanceToBilbao
Indicates the measured distance between a given entity’s location and the city of Bilbao.
- 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_69ef6a52fa708190934a32308d2c92dc |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69fcda3699948190adb57625bae08091 |
completed | May 7, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fd16d08190b0aca6e19a632e99 |
completed | May 7, 2026, 6:25 p.m. |
Created at: April 27, 2026, 4:34 p.m.