Triple
T13179742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AllWISE Source Catalog |
E313691
|
entity |
| Predicate | usesDataFrom |
P399
|
FINISHED |
| Object | WISE |
E1027637
|
NE 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: WISE | Statement: [AllWISE Source Catalog, usesDataFrom, WISE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WISE Context triple: [AllWISE Source Catalog, usesDataFrom, WISE]
-
A.
WISE
chosen
WISE is a NASA space telescope that conducted an all-sky survey in infrared light to discover and catalog objects such as asteroids, stars, and distant galaxies.
-
B.
WIT
WIT is the New York Stock Exchange ticker symbol for Wipro Limited, a major Indian multinational information technology services and consulting company.
-
C.
WIJ
WIJ is the National Rail station code for Willesden Junction, a major interchange station in northwest London served by both Overground and mainline rail services.
-
D.
WIS
WIS is the vehicle registration code used on license plates for the district of Nordwestmecklenburg in the German state of Mecklenburg-Vorpommern.
-
E.
WIS
WIS is the World Meteorological Organization’s global information system for sharing and distributing meteorological, hydrological, and related environmental data.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c47e79c81908031d3e6f1cfd64f |
completed | April 10, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a2e415481908ad1036376f702dc |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:14 p.m.