Triple
T20517789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Federation of Planets |
E503724
|
entity |
| Predicate | memberWorldsCount |
P117199
|
FINISHED |
| Object | over one hundred member worlds |
—
|
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 one hundred member worlds | Statement: [United Federation of Planets, memberWorldsCount, over one hundred member worlds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memberWorldsCount Context triple: [United Federation of Planets, memberWorldsCount, over one hundred member worlds]
-
A.
hasWorldCount
chosen
Indicates that an entity is associated with a specific number of worlds.
-
B.
memberAssociationCount
Indicates the number of associations or group memberships linked to a given member.
-
C.
numberOfRegionalMembers
Indicates the quantity of members associated with or belonging to a specific region within a given context.
-
D.
hasNumberOfCountries
Indicates the relationship that specifies how many countries are associated with or contained within a given entity.
-
E.
countryRepresentedCount
Indicates the number of distinct countries that are represented or associated with a given entity.
- 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f42db688190a3ccfba5601e8bf3 |
completed | April 20, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:36 a.m.