Triple
T2655132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kermadec Islands |
E53989
|
entity |
| Predicate | distanceFromTongaKilometres |
P41997
|
FINISHED |
| Object | about 900 |
—
|
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 900 | Statement: [Kermadec Islands, distanceFromTongaKilometres, about 900]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTongaKilometres Context triple: [Kermadec Islands, distanceFromTongaKilometres, about 900]
-
A.
distanceFromNewZealandMainland_km
Indicates the distance, measured in kilometers, between an entity’s location and the mainland of New Zealand.
-
B.
distanceToHoniaraApprox
Indicates an approximate distance measurement between a given entity’s location and the location of Honiara.
-
C.
distanceFromJuanFernandezIslands_km
Indicates the distance, measured in kilometers, between an entity and the Juan Fernández Islands.
-
D.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
E.
distanceToSriLanka
Indicates the spatial distance between a given entity’s location and the country of Sri Lanka.
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abda0ba2208190ad87763ecbef8c3c |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd815d06481909535c02b0aba8553 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abda0a13308190a986df86270258a7 |
completed | March 7, 2026, 7:55 a.m. |
Created at: March 6, 2026, 9:53 p.m.