Triple
T23244318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hipparcos Catalogue |
E581539
|
entity |
| Predicate | containsPhotometricQualityFlags |
P143859
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hipparcos Catalogue, containsPhotometricQualityFlags, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsPhotometricQualityFlags Context triple: [Hipparcos Catalogue, containsPhotometricQualityFlags, yes]
-
A.
hasPerceptualQuality
Indicates that something possesses a particular sensory or perceptual characteristic, such as a color, sound, texture, taste, or smell.
-
B.
hasPhotometry
chosen
Indicates that an entity possesses or is associated with photometric data or measurements.
-
C.
hasQualityCriterion
Indicates that something is associated with a specific standard or criterion used to judge its quality.
-
D.
hasQuantizationCondition
Indicates that a system, parameter, or quantity is constrained to take on only discrete (often integer-related) values according to a specific quantization rule or condition.
-
E.
hasPhotogenicFeature
Indicates that an entity possesses a visual characteristic or attribute that is especially attractive or appealing when photographed.
- 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193ee37c8819091f799506fa532da |
completed | April 29, 2026, 5:15 a.m. |
| PD | Predicate disambiguation | batch_69effcdadec0819092ec1749ee453b4e |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:10 p.m.