Triple
T26367234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Formentor, Mallorca |
E660372
|
entity |
| Predicate | distanceFromPortDePollenca_km |
P196111
|
FINISHED |
| Object | approximately 14 |
—
|
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 14 | Statement: [Formentor, Mallorca, distanceFromPortDePollenca_km, approximately 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromPortDePollenca_km Context triple: [Formentor, Mallorca, distanceFromPortDePollenca_km, approximately 14]
-
A.
distanceTo Palma de Mallorca (approximate km)
Indicates the approximate distance in kilometers between an entity’s location and Palma de Mallorca.
-
B.
distanceFromSkopelosTown_km
Indicates the distance, measured in kilometers, between an entity and Skopelos Town.
-
C.
distanceFromCórdobaCity
Indicates the spatial distance between an entity and the city of Córdoba.
-
D.
distanceToIbiza
Indicates the spatial distance between a given entity’s location and the location of Ibiza.
-
E.
distanceToMálaga
Indicates the spatial distance between a given entity and the location of Málaga.
- 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_69ee8126d52c8190bc0b34337c2c9aa8 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69fe08d2b2e48190ac7be6d62d4a44a3 |
completed | May 8, 2026, 4:01 p.m. |
| PD | Predicate disambiguation | batch_69fe06cd3af08190ae25de0dc0cdd573 |
completed | May 8, 2026, 3:52 p.m. |
| PDg | Predicate description generation | batch_69fe08d1b3f881908eccb74cb0d246dc |
completed | May 8, 2026, 4:01 p.m. |
Created at: April 26, 2026, 10:55 p.m.