Triple
T6010264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CMS surface assembly hall |
E133812
|
entity |
| Predicate | hasCraneCapacity |
P68727
|
FINISHED |
| Object | suitable for very heavy detector modules |
—
|
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: suitable for very heavy detector modules | Statement: [CMS surface assembly hall, hasCraneCapacity, suitable for very heavy detector modules]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCraneCapacity Context triple: [CMS surface assembly hall, hasCraneCapacity, suitable for very heavy detector modules]
-
A.
cargoCapacityFeature
Indicates that an entity has a feature specifying how much cargo it can carry or accommodate.
-
B.
designedCargoCapacity
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
-
C.
maximumTonnageLimitedBy
Indicates that the maximum allowable tonnage of one entity is constrained or capped by the capacity or limit specified by another entity.
-
D.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
-
E.
weightLimitInKilograms
Indicates the maximum allowable weight for something, expressed in kilograms.
- 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_69c0087361a48190905c6b55969852b8 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f4ffa008190a8ef701b82260219 |
completed | March 22, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69c049e4daf4819099bf870dc700e0a2 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8c5bfc8190b986a7071d1b23e3 |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:06 p.m.