Triple
T20997959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Civilian Public Service camp |
E517198
|
entity |
| Predicate | hasNumberOfSites |
P14032
|
FINISHED |
| Object | over 150 camps and units |
—
|
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 150 camps and units | Statement: [Civilian Public Service camp, hasNumberOfSites, over 150 camps and units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfSites Context triple: [Civilian Public Service camp, hasNumberOfSites, over 150 camps and units]
-
A.
numberOfSites
chosen
Indicates the total count of distinct sites associated with or involved in the given entity or context.
-
B.
hasNumberOfCentres
Indicates the relationship specifying how many centers (or central units/locations) are associated with a given entity.
-
C.
hasSiteStatus
Indicates the current operational or condition status assigned to a particular site.
-
D.
hasNumberOfCampsites
Indicates the specific quantity of campsites associated with a given place, facility, or area.
-
E.
hasRepresentativeSite
Indicates that an entity is associated with a specific site that serves as its primary or official representative location.
- 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_69e0b5006e2881909fc2383f841740cc |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc22ca6081908bf054ddcfea9e19 |
completed | April 21, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69e5dbec80708190a49bccab7ff97e7b |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 1:51 p.m.