Triple
T37496993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Eyasi |
E931851
|
entity |
| Predicate | primaryEconomicActivityInArea |
P114644
|
FINISHED |
| Object | pastoralism |
—
|
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: pastoralism | Statement: [Lake Eyasi, primaryEconomicActivityInArea, pastoralism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryEconomicActivityInArea Context triple: [Lake Eyasi, primaryEconomicActivityInArea, pastoralism]
-
A.
primarySectorActivity
Indicates the main industry or sector in which an entity primarily conducts its activities or operations.
-
B.
regionalEconomyActivity
chosen
Indicates the type or level of economic activity occurring within a specific geographic region.
-
C.
primaryEconomicHinterland
Indicates that one place serves as the main surrounding area that economically supports, supplies, or is influenced by another place.
-
D.
regionalEconomyType
Indicates the type or classification of an economy associated with a specific region.
-
E.
economicSectorDominant
Indicates that one economic sector holds a leading or controlling position relative to others in terms of influence, output, or importance.
- 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_69f76ec457a4819094eeb3aed9baac11 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:17 p.m.