Triple
T15028821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pampilhosa da Serra |
E378286
|
entity |
| Predicate | distanceToCoimbra |
P116447
|
FINISHED |
| Object | approximately 80 km east |
—
|
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 80 km east | Statement: [Pampilhosa da Serra, distanceToCoimbra, approximately 80 km east]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCoimbra Context triple: [Pampilhosa da Serra, distanceToCoimbra, approximately 80 km east]
-
A.
distanceFromPorto
Indicates the measured distance between a given place or entity and the city of Porto.
-
B.
distanceFromLisbon
Indicates the measured spatial distance between a given entity’s location and the city of Lisbon.
-
C.
distanceToSalamanca
Indicates the spatial distance between a given entity and the location of Salamanca.
-
D.
distanceToMadrid
Indicates the physical distance between a given location or entity and the city of Madrid.
-
E.
distanceToValladolid
Indicates the spatial distance between a given entity or location and the city of Valladolid.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e0e8c88190ac6f5786b4d4040f |
completed | April 15, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:58 a.m.