Triple
T18956515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HD 24760 |
E463792
|
entity |
| Predicate | hasBinaryEccentricity |
P2030
|
FINISHED |
| Object | about 0.52 |
—
|
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 0.52 | Statement: [HD 24760, hasBinaryEccentricity, about 0.52]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBinaryEccentricity Context triple: [HD 24760, hasBinaryEccentricity, about 0.52]
-
A.
hasEccentricity
chosen
Indicates that an object or orbit possesses a specific degree of deviation from being perfectly circular, quantified by its eccentricity value.
-
B.
hasEccentricityPeriod
Indicates a relationship where an object is associated with a specific orbital eccentricity and its corresponding orbital period.
-
C.
isEccentric
Indicates that an entity behaves or appears in a way that deviates noticeably from conventional or expected norms.
-
D.
hasEccentricSetting
Indicates that something is characterized by an unusual, unconventional, or quirky setting or environment.
-
E.
eccentricityClass
Indicates the classification of how unconventional or atypical an entity’s behavior, properties, or characteristics are relative to a defined norm.
- 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_69d8dcffc278819086792a4ebfddfafa |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d5cdf2d08190a0aecd3fa5335a75 |
completed | April 20, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, noon