Triple
T27881108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Duration Exposure Facility |
E705091
|
entity |
| Predicate | numberOfPrincipalInvestigations |
P35717
|
FINISHED |
| Object | over 200 |
—
|
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: over 200 | Statement: [Long Duration Exposure Facility, numberOfPrincipalInvestigations, over 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPrincipalInvestigations Context triple: [Long Duration Exposure Facility, numberOfPrincipalInvestigations, over 200]
-
A.
numberOfInvestigations
chosen
Indicates the count of investigations associated with or conducted by a given entity.
-
B.
numberOfExperiments
Indicates the total count of experiments associated with or performed in a given context or entity.
-
C.
studiesQuantity
Indicates that an entity engages in the study or examination of a particular quantity or measurable amount.
-
D.
numberOfResearchCentres
Indicates the quantity of research centres associated with a given entity.
-
E.
designedToInvestigate
Indicates that something was intentionally created or structured for the purpose of examining, exploring, or studying a particular subject, phenomenon, or question.
- 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_69ef84111bb4819084298f994b31c62f |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69ff255b84788190a94682f4efe1d0b8 |
completed | May 9, 2026, 12:15 p.m. |
| PD | Predicate disambiguation | batch_69ff24f3ab108190bb017a656cff3d82 |
completed | May 9, 2026, 12:13 p.m. |
Created at: April 27, 2026, 6:30 p.m.