Triple
T36894962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Forest People |
E911865
|
entity |
| Predicate | fieldworkCountry |
P186737
|
FINISHED |
| Object | Democratic Republic of the Congo |
—
|
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: Democratic Republic of the Congo | Statement: [The Forest People, fieldworkCountry, Democratic Republic of the Congo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldworkCountry Context triple: [The Forest People, fieldworkCountry, Democratic Republic of the Congo]
-
A.
workFromCountry
Indicates that an entity performs their work or job while being physically located in a specified country.
-
B.
countryFeatured
Indicates that a particular country is highlighted or given special prominence in a given context or presentation.
-
C.
repositoryCountry
Indicates the country in which a repository is located or maintained.
-
D.
worksInCountry
Indicates that an entity performs its work or professional activities within the specified country.
-
E.
countryImplements
Indicates that a country puts into effect, enforces, or carries out a specific policy, law, agreement, standard, or measure.
- 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_69f76e841b54819097e7fa768bbc70b2 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fa0a7b00948190a257273d9968c5d7 |
completed | May 5, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69f9fec9c9488190ae2a349651a02782 |
completed | May 5, 2026, 2:29 p.m. |
| PDg | Predicate description generation | batch_69fa0a799b9081909bfa8293a22c4b00 |
completed | May 5, 2026, 3:19 p.m. |
Created at: May 3, 2026, 4:13 p.m.