Triple
T18481890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | damped Lyman-alpha system |
E451580
|
entity |
| Predicate | hasTypicalRedshiftRange |
P131822
|
FINISHED |
| Object | high redshift (z ≳ 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: high redshift (z ≳ 2) | Statement: [damped Lyman-alpha system, hasTypicalRedshiftRange, high redshift (z ≳ 2)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalRedshiftRange Context triple: [damped Lyman-alpha system, hasTypicalRedshiftRange, high redshift (z ≳ 2)]
-
A.
redshift_z
Indicates the cosmological redshift value associated with an object or event, representing how much its emitted light has been stretched by the expansion of the universe.
-
B.
hasSpectralTypeRange
Indicates that an entity is associated with a specified range of spectral types rather than a single, discrete spectral classification.
-
C.
hasLowLuminosity
Indicates that an entity emits relatively little light or energy compared to a typical or reference level.
-
D.
hasObservationWavelength
Indicates the specific wavelength at which an observation or measurement is made or recorded.
-
E.
hasFocalRatioRange
Indicates that an entity is associated with a range of possible focal ratios, specifying the minimum and maximum f-number values it can have.
- F. None of above. chosen
Provenance (4 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e531d3d13c81909c52d797360b840a |
completed | April 19, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69e469d671088190b619de96ea6f92ab |
completed | April 19, 2026, 5:36 a.m. |
| PDg | Predicate description generation | batch_69e46d2aa72c8190a40854a7a52081e2 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 11:35 a.m.