Triple
T36485589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbus External Payload Facility |
E898924
|
entity |
| Predicate | numberOfPayloadSites |
P14032
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Columbus External Payload Facility, numberOfPayloadSites, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPayloadSites Context triple: [Columbus External Payload Facility, numberOfPayloadSites, 4]
-
A.
numberOfSites
chosen
Indicates the total count of distinct sites associated with or involved in the given entity or context.
-
B.
payloadCount
Indicates the number of payload items associated with or carried by a given entity or operation.
-
C.
numberWithinSite
Indicates that an entity has a specific identifying number or position assigned within the context of a particular site or location.
-
D.
numberOfEntities
Indicates the total count of distinct entities involved in or associated with a given context or situation.
-
E.
numberOfPointSources
Indicates the total count of distinct point sources involved or present in a given context or system.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:10 p.m.