Triple
T15598597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dark Energy Spectroscopic Instrument |
E374970
|
entity |
| Predicate | targetNumberOfObjects |
P9099
|
FINISHED |
| Object | about 35 million |
—
|
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 35 million | Statement: [Dark Energy Spectroscopic Instrument, targetNumberOfObjects, about 35 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetNumberOfObjects Context triple: [Dark Energy Spectroscopic Instrument, targetNumberOfObjects, about 35 million]
-
A.
numberOfTargets
chosen
Indicates the quantity of target entities associated with or affected by a given subject or event.
-
B.
goalNumber
Indicates that an entity is associated with a specific target or objective quantified as a number.
-
C.
availabilityTarget
Indicates that something is the intended object, resource, or condition whose availability is being specified, monitored, or constrained.
-
D.
usesObjective
Indicates that an agent employs or applies a particular object, tool, or resource to carry out an action or achieve a goal.
-
E.
plannedTarget
Indicates that one entity has been designated or selected as the intended target or objective of another entity’s planned action or operation.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e609ab081909feb486a57439960 |
completed | April 16, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69deda844af081909e658ebc9d9b403d |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:12 a.m.