Triple
T19085948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alter do Chão |
E467148
|
entity |
| Predicate | distanceFromSantarém |
P134320
|
FINISHED |
| Object | approximately 35 kilometers |
—
|
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: approximately 35 kilometers | Statement: [Alter do Chão, distanceFromSantarém, approximately 35 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromSantarém Context triple: [Alter do Chão, distanceFromSantarém, approximately 35 kilometers]
-
A.
distanceFromLisbon
Indicates the measured spatial distance between a given entity’s location and the city of Lisbon.
-
B.
distanceFromPorto
Indicates the measured distance between a given place or entity and the city of Porto.
-
C.
distanceToLeiria
Indicates the spatial distance between a given entity and the location of Leiria.
-
D.
distanceToCoimbra
Indicates the spatial distance between a given entity and the location of Coimbra.
-
E.
distanceToFátima
Indicates the spatial distance between a given entity and the location of Fátima.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e347ee288190a3e935ff89ca94aa |
completed | April 20, 2026, 8:26 a.m. |
| PD | Predicate disambiguation | batch_69e4b9a604308190a3235184f9f2c056 |
completed | April 19, 2026, 11:16 a.m. |
| PDg | Predicate description generation | batch_69e4bfe8a06081909fd5c28a33e9f218 |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:04 p.m.