Triple
T33506884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sex on the Moon |
E858135
|
entity |
| Predicate | describesFacility |
P191032
|
FINISHED |
| Object | Lunar Sample Laboratory Facility |
—
|
NE NERFINISHED |
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: Lunar Sample Laboratory Facility | Statement: [Sex on the Moon, describesFacility, Lunar Sample Laboratory Facility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describesFacility Context triple: [Sex on the Moon, describesFacility, Lunar Sample Laboratory Facility]
-
A.
identifiesFacility
Indicates that one entity serves to recognize, specify, or distinguish a particular facility as the relevant or associated one.
-
B.
servesFacility
Indicates that one entity provides services or support to a particular facility as its client, target, or area of operation.
-
C.
facilityCharacteristic
Indicates that a facility possesses a particular attribute, feature, or quality that characterizes it.
-
D.
displayFacility
Indicates that an entity presents, exhibits, or makes another entity visible or accessible, typically within a particular environment or interface.
-
E.
designedFacilityType
Indicates the type or category of facility that something (such as a plan, system, or component) is specifically designed for.
- 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_69f3497721848190978fbee5e0a526f8 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
| PDg | Predicate description generation | batch_69fcd866dd248190bff61c43bee93f54 |
completed | May 7, 2026, 6:22 p.m. |
Created at: May 1, 2026, 1:38 a.m.