Triple
T34911944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WASP-39b |
E1006894
|
entity |
| Predicate | hasPhotometricObservations |
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: [WASP-39b, hasPhotometricObservations, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotometricObservations Context triple: [WASP-39b, hasPhotometricObservations, yes]
-
A.
hasPhotometry
chosen
Indicates that an entity possesses or is associated with photometric data or measurements.
-
B.
hasSpectralObservation
Indicates that a spectral measurement or observation has been made of an entity, linking it to the corresponding spectral data or record.
-
C.
usesPhotometryFrom
Indicates that one entity bases its measurements, analyses, or results on photometric data obtained from another entity.
-
D.
hasLightcurveMeasurements
Indicates that an entity has associated lightcurve measurements, representing recorded variations in its brightness over time.
-
E.
hasObservationWavelength
Indicates the specific wavelength at which an observation or measurement is made or recorded.
- 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_69f76dc1b4a081909b4c6e4d8ec0aa2d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4 p.m.