Triple
T36760971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stiffbeards |
E908198
|
entity |
| Predicate | hasGeographicSpecificity |
P196027
|
FINISHED |
| Object | unspecified in primary texts |
—
|
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: unspecified in primary texts | Statement: [Stiffbeards, hasGeographicSpecificity, unspecified in primary texts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGeographicSpecificity Context triple: [Stiffbeards, hasGeographicSpecificity, unspecified in primary texts]
-
A.
isGeographicallySpecific
Indicates that something is limited to or uniquely associated with a particular geographic location or area.
-
B.
hasGeographicType
Indicates that an entity is associated with or classified by a specific type or category of geographic feature or area.
-
C.
geographicRelevance
Indicates that something has a meaningful connection or applicability to a specific geographic area or location.
-
D.
hasGeographicBasis
Indicates that something is grounded in, derived from, or defined by a particular geographic location or area.
-
E.
hasGeographicalLocation
Indicates that an entity is situated in, or associated with, a specific geographical place or area.
- 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_69f76e779bec8190be0e1f87a131e0f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe00dad1708190b6522476bebb43af |
completed | May 8, 2026, 3:27 p.m. |
| PD | Predicate disambiguation | batch_69fdfc3717f48190bb50ac2919c8ef95 |
completed | May 8, 2026, 3:07 p.m. |
| PDg | Predicate description generation | batch_69fe00d8d8248190a63c12aa2c2f7c0c |
completed | May 8, 2026, 3:27 p.m. |
Created at: May 3, 2026, 4:12 p.m.