Triple
T14387851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fahrenheit |
E356770
|
entity |
| Predicate | zeroPointDefinition |
P65427
|
FINISHED |
| Object | originally based on brine freezing point |
—
|
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: originally based on brine freezing point | Statement: [Fahrenheit, zeroPointDefinition, originally based on brine freezing point]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zeroPointDefinition Context triple: [Fahrenheit, zeroPointDefinition, originally based on brine freezing point]
-
A.
zeroDefinition
Indicates that something has no defined value, quantity, or specification within the given context.
-
B.
pointDefinition
Indicates that one entity serves as the defining description or specification of a particular point in another entity.
-
C.
formsZeroPointFor
chosen
Indicates that one entity serves as the reference or origin point (zero point) for measuring or defining another entity.
-
D.
zeroConcept
Indicates a conceptual or abstract entity that has no concrete instances or realizations in the given context.
-
E.
isZeroFor
Indicates that a given value, expression, or function evaluates to zero when applied to or considered with respect to a specified entity or context.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90283b9c8190b50d30ad58bfe085 |
completed | April 14, 2026, 7:06 p.m. |
| PD | Predicate disambiguation | batch_69de2aa024c48190805df6a9d63deb10 |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:16 a.m.