Triple
T5260014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Two Micron All Sky Survey |
E118799
|
entity |
| Predicate | numberOfPointSources |
P62580
|
FINISHED |
| Object | over 470 million |
—
|
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: over 470 million | Statement: [Two Micron All Sky Survey, numberOfPointSources, over 470 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPointSources Context triple: [Two Micron All Sky Survey, numberOfPointSources, over 470 million]
-
A.
pointSource
Indicates that an entity acts as a localized origin or emitter of some quantity (such as light, sound, or radiation) concentrated at a single point in space.
-
B.
numberOfSites
Indicates the total count of distinct sites associated with or involved in the given entity or context.
-
C.
hasNumberOfPoints
Indicates that an entity is associated with a specific count of points it possesses or comprises.
-
D.
numberOfTargets
Indicates the quantity of target entities associated with or affected by a given subject or event.
-
E.
numberOfRays
Indicates the count of rays associated with or emitted by a given entity.
- 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bcced6881909bdb7ac5471a37fe |
completed | March 20, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69bd77c55224819096c0bcfcfae79bd3 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd7bcabe58819096255672664513b1 |
completed | March 20, 2026, 4:54 p.m. |
Created at: March 20, 2026, 1:50 p.m.