Triple
T23993572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manjack |
E605130
|
entity |
| Predicate | primaryLocationWithinGuinea-Bissau |
P154542
|
FINISHED |
| Object | northern Guinea-Bissau |
—
|
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: northern Guinea-Bissau | Statement: [Manjack, primaryLocationWithinGuinea-Bissau, northern Guinea-Bissau]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryLocationWithinGuinea-Bissau Context triple: [Manjack, primaryLocationWithinGuinea-Bissau, northern Guinea-Bissau]
-
A.
primaryLocationInSudan
Indicates that the primary or main location associated with an entity is situated within the country of Sudan.
-
B.
regionWithinMozambique
Indicates that one region is geographically located within the national boundaries of Mozambique.
-
C.
nearestMajorTownInGuinea
Indicates that one location is the closest significant town within Guinea to another specified place.
-
D.
statusInEquatorialGuinea
Indicates the legal, social, or functional standing or condition that something or someone has within the context of Equatorial Guinea.
-
E.
primaryLocationInChad
Indicates that the referenced entity’s main or most significant location is situated within the country of Chad.
- 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_69e295463f7c8190b1c19dbd114641b9 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d38ce7fc8190a488991b6f61416b |
completed | April 29, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e348b548190b76e50f9b611f76d |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 9:38 p.m.