Triple
T32257231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hubble Deep Field |
E824056
|
entity |
| Predicate | totalExposureTime |
P43134
|
FINISHED |
| Object | about 342,000 seconds |
—
|
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 342,000 seconds | Statement: [Hubble Deep Field, totalExposureTime, about 342,000 seconds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalExposureTime Context triple: [Hubble Deep Field, totalExposureTime, about 342,000 seconds]
-
A.
exposureTime
Indicates the duration for which a subject or object is exposed to a particular condition, influence, or medium.
-
B.
durationTotal
chosen
Indicates the overall length of time for which an event, process, or state persists, typically aggregating all its constituent durations.
-
C.
shutterSpeed
Indicates the exposure time setting of a camera, defining how long the shutter remains open during an image capture.
-
D.
timeSpanOfFootage
Indicates the duration of time covered by a given piece of footage.
-
E.
exposureModes
Indicates the different ways or conditions under which an entity can be exposed to another entity, factor, or influence.
- 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_69f3490db0748190bfef6e50c95d39d3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7817daf00819098936402e75ab0a6 |
completed | May 3, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 1, 2026, 12:41 a.m.