Triple
T28943552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GW150914 |
E730519
|
entity |
| Predicate | skyLocalizationArea |
P25535
|
FINISHED |
| Object | about 600 square degrees |
—
|
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 600 square degrees | Statement: [GW150914, skyLocalizationArea, about 600 square degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skyLocalizationArea Context triple: [GW150914, skyLocalizationArea, about 600 square degrees]
-
A.
所在地エリア
Indicates the geographical area or region in which an entity is located or based.
-
B.
zone
Indicates that an entity is located within, associated with, or assigned to a particular geographic or conceptual area or zone.
-
C.
scoutingArea
Indicates that an entity is actively exploring or surveying a specified area, typically to gather information or assess conditions there.
-
D.
arealRegion
chosen
Indicates that something occupies or pertains to a specific two-dimensional geographic or spatial area.
-
E.
regionInGame
Indicates that a specific region or area exists within or is part of a particular game.
- 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_69f043ea0aa88190a25acbf46157995a |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f65b85839c8190be57052eaef1d74f |
completed | May 2, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 8:38 a.m.