Triple
T17907392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sector V |
E447735
|
entity |
| Predicate | hasDemographicInUniverse |
P7875
|
FINISHED |
| Object | pre‑teen children |
—
|
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: pre‑teen children | Statement: [Sector V, hasDemographicInUniverse, pre‑teen children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDemographicInUniverse Context triple: [Sector V, hasDemographicInUniverse, pre‑teen children]
-
A.
hasDemographic
chosen
Indicates that an entity is associated with or characterized by a particular demographic group or attribute.
-
B.
hasFictionalDemographic
Indicates that an entity is associated with a demographic group that is fictional or exists only within a created narrative or imagined context.
-
C.
hasDemographicPresenceIn
Indicates that a particular demographic group exists or is represented within a specified geographic area or population context.
-
D.
ethnicityInUniverse
Indicates that, within a given fictional or defined universe, a particular entity is associated with or belongs to a specified ethnicity as understood in that universe.
-
E.
demographicsIn
Indicates that demographic information is associated with or applies within a specified geographic or organizational area.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49e9d458881909e35e1c7a6e85436 |
completed | April 19, 2026, 9:21 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
Created at: April 10, 2026, 10:19 a.m.