Triple
T28880721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GW170814 |
E732408
|
entity |
| Predicate | hasMassRatio |
P143347
|
FINISHED |
| Object | ~1.2 |
—
|
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: ~1.2 | Statement: [GW170814, hasMassRatio, ~1.2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMassRatio Context triple: [GW170814, hasMassRatio, ~1.2]
-
A.
hasApproximateMassRatio
chosen
Indicates that one entity’s mass is approximately proportional to, or in a specified ratio with, the mass of another entity, within an accepted tolerance.
-
B.
hasMassScale
Indicates that an entity is associated with a particular mass measurement scale or system used to quantify its mass.
-
C.
hasMassFraction
Indicates that a specified portion of a substance’s total mass is attributable to a particular component or constituent.
-
D.
hasMasses
Indicates that one entity possesses or is associated with one or more masses (quantities of matter).
-
E.
hasTypeOfMass
Indicates that one entity possesses or is characterized by a particular kind or category of mass.
- 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_69f05b06807c81909b4bbd4c20403a2b |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69feecf1bb248190ba30f0bb1d22ee08 |
completed | May 9, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69feea5f27748190b223ee4e3ba5a678 |
completed | May 9, 2026, 8:03 a.m. |
Created at: April 28, 2026, 7:43 a.m.