Triple
T1887001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Métro Line 1 |
E39985
|
entity |
| Predicate | lengthInKm |
P33049
|
FINISHED |
| Object | 16.5 |
—
|
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: 16.5 | Statement: [Paris Métro Line 1, lengthInKm, 16.5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lengthInKm Context triple: [Paris Métro Line 1, lengthInKm, 16.5]
-
A.
range_km
Indicates the maximum distance, measured in kilometers, over which something can operate, travel, or be effective.
-
B.
navigableLengthApproxKm
Indicates the approximate distance, measured in kilometers, over which something (typically a waterway) can be navigated.
-
C.
hasMainStraightLengthKm
Indicates the length in kilometers of the primary or main straight segment associated with an entity.
-
D.
mainStraightLengthKm
Indicates the length, measured in kilometers, of the primary straight segment associated with the entity.
-
E.
trailLengthApprox
Indicates an approximate measurement of the total length of a trail.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb121a3cc81909c60ac65627142d1 |
completed | March 7, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69abafe61bc48190ac9ead027df930e1 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb11bfd2c8190a805372589f73238 |
completed | March 7, 2026, 5:01 a.m. |
Created at: March 4, 2026, 7:34 p.m.