Triple
T37939129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | São Mateus |
E946432
|
entity |
| Predicate | hasOilRelatedActivity |
P156693
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [São Mateus, hasOilRelatedActivity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOilRelatedActivity Context triple: [São Mateus, hasOilRelatedActivity, true]
-
A.
containsOilField
Indicates that one entity geographically includes or encompasses an oil field within its boundaries.
-
B.
hasOilTerminal
Indicates that one entity possesses, hosts, or contains an oil terminal used for storing or transferring oil.
-
C.
hasOilHouse
Indicates that one entity possesses or includes a building or structure designated as an oil house.
-
D.
hasOnshoreOilAndGasProduction
chosen
Indicates that an entity engages in or possesses facilities for extracting oil and/or natural gas from onshore (land-based) fields.
-
E.
hasNearbyOilAndGasFields
Indicates that an entity is located close to one or more oil and gas extraction fields.
- 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_69f76ef531ac8190ae6d99e5786e76ec |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc7b78f9481909f4f8fc2e3fdcde1 |
completed | May 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69fbbd18c9908190928d274f8731dfa8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:20 p.m.