Triple
T10285389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casablanca, French Morocco |
E241212
|
entity |
| Predicate | hadFunctionAs |
P20953
|
FINISHED |
| Object | naval base |
—
|
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: naval base | Statement: [Casablanca, French Morocco, hadFunctionAs, naval base]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadFunctionAs Context triple: [Casablanca, French Morocco, hadFunctionAs, naval base]
-
A.
hadFunction
chosen
Indicates that an entity previously served or fulfilled a particular role, purpose, or function.
-
B.
has
Indicates that one entity possesses, owns, contains, or includes another entity as part of its state or composition.
-
C.
hadNo
Indicates that one entity completely lacked or did not possess another entity, attribute, or relationship.
-
D.
hadOrgan
Indicates that an entity previously possessed or contained a specific organ as part of its body.
-
E.
endedFunctionallyWith
Indicates that a process, event, or relationship has effectively concluded in practice, even if it has not been formally or officially terminated.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f117708190928f92ae2611d724 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:40 a.m.