Triple
T32257238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hubble Deep Field |
E824056
|
entity |
| Predicate | numberOfDetectedObjects |
P203513
|
FINISHED |
| Object | about 3,000 galaxies |
—
|
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: about 3,000 galaxies | Statement: [Hubble Deep Field, numberOfDetectedObjects, about 3,000 galaxies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDetectedObjects Context triple: [Hubble Deep Field, numberOfDetectedObjects, about 3,000 galaxies]
-
A.
numberOfDetectors
Indicates the quantity of detectors associated with or involved in a given entity or system.
-
B.
numberOfTargets
Indicates the quantity of target entities associated with or affected by a given subject or event.
-
C.
numberOfSensors
Indicates the quantity of sensors associated with or contained by a given entity.
-
D.
numberOfMainDetectors
Indicates the quantity of primary detectors associated with or used in a given context or system.
-
E.
numberOfInstances
Indicates the quantity or count of distinct occurrences or instances associated with a given entity or context.
- 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_69f3490db0748190bfef6e50c95d39d3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a019579463c8190b51e39183b57bbaf |
completed | May 11, 2026, 8:38 a.m. |
| PD | Predicate disambiguation | batch_6a0192d309488190a3d86c93e7138c77 |
completed | May 11, 2026, 8:26 a.m. |
| PDg | Predicate description generation | batch_6a019578545c8190964a8b9087d3a46a |
completed | May 11, 2026, 8:38 a.m. |
Created at: May 1, 2026, 12:41 a.m.