Triple
T9694139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lafkenche |
E234604
|
entity |
| Predicate | culturalIdentityBasedOn |
P56388
|
FINISHED |
| Object | maritime livelihoods |
—
|
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: maritime livelihoods | Statement: [Lafkenche, culturalIdentityBasedOn, maritime livelihoods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: culturalIdentityBasedOn Context triple: [Lafkenche, culturalIdentityBasedOn, maritime livelihoods]
-
A.
hasStrongCulturalIdentity
Indicates that an entity possesses a well-defined, deeply rooted, and strongly maintained sense of belonging to a particular culture or cultural tradition.
-
B.
cultureOfOrigin
chosen
Indicates the cultural background or tradition from which an entity originates or is derived.
-
C.
hasAuthorCulturalIdentity
Indicates that an author is associated with a particular cultural identity or background.
-
D.
ethnoreligiousIdentity
Indicates a relationship where an entity is characterized by a combined ethnic and religious group identity.
-
E.
racialIdentity
Indicates the relationship between an entity and the racial group or classification with which it is identified or categorized.
- 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d348868819083aec7a5da8c455b |
completed | April 1, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b840f081909f66bf0b66d17d9b |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:17 p.m.