Triple
T24465529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tétouan Province |
E616956
|
entity |
| Predicate | hasHistoricTiesTo |
P7843
|
FINISHED |
| Object | Tétouan |
—
|
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: Tétouan | Statement: [Tétouan Province, hasHistoricTiesTo, Tétouan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricTiesTo Context triple: [Tétouan Province, hasHistoricTiesTo, Tétouan]
-
A.
hasHistoricalTieTo
chosen
Indicates a relationship where one entity is historically connected or linked to another through past events, associations, or influences.
-
B.
hasNegativeHistoricalAssociation
Indicates that one entity is historically linked to another in a way that is viewed as harmful, problematic, or disreputable.
-
C.
historicalRelationsWith
Indicates a relationship where one entity has documented or recognized connections, interactions, or associations with another entity in the past.
-
D.
hasSharedBorderHistoryWith
Indicates that two entities have a history of sharing a common border or boundary at some point in time.
-
E.
hasHistoricalArc
Indicates that something unfolds over time in a way that forms a coherent, meaningful historical development or narrative.
- 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_69e2d7f197588190889a03e620558059 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2993ecd988190991598832b29a131 |
completed | April 29, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69f287d76c7c81909494f12e606a9149 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:19 a.m.