Triple
T28880712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GW170814 |
E732408
|
entity |
| Predicate | hasPolarizationMeasurement |
P38744
|
FINISHED |
| Object | constrains tensor polarizations |
—
|
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: constrains tensor polarizations | Statement: [GW170814, hasPolarizationMeasurement, constrains tensor polarizations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPolarizationMeasurement Context triple: [GW170814, hasPolarizationMeasurement, constrains tensor polarizations]
-
A.
hasPolarSetting
Indicates that something is configured or oriented according to a polar coordinate or polar reference system.
-
B.
hasPolarCoverage
Indicates that an entity includes or provides coverage, presence, or applicability in polar regions.
-
C.
polarizationModes
chosen
Indicates the specific polarization states or configurations associated with a signal, wave, or optical/electromagnetic system.
-
D.
polarizationLevel
Indicates the degree or intensity of polarization present in a given context, such as between opinions, groups, or signals.
-
E.
isPolar
Indicates that something possesses a separation of electric charge resulting in distinct positive and negative regions (i.e., has polarity).
- 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_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
Created at: April 28, 2026, 7:43 a.m.