Triple
T18497608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PMM Leonardo |
E451988
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | PMM |
—
|
NE NERFINISHED |
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: PMM | Statement: [PMM Leonardo, hasAlternativeName, PMM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PMM Context triple: [PMM Leonardo, hasAlternativeName, PMM]
-
A.
PMM
chosen
PMM is the commonly used acronym for Perpignan Méditerranée Métropole, an intercommunal urban community centered on the city of Perpignan in southern France.
-
B.
PMB
PMB is the abbreviation for Pure Michigan Byway, a designation for particularly scenic or culturally significant roads in the state of Michigan.
-
C.
PMO
PMO is the IATA airport code for Falcone–Borsellino Airport serving Palermo, Sicily, Italy.
-
D.
PDM
PDM is a modern Python package and dependency manager that emphasizes PEP 582 support and a streamlined, pyproject.toml-based workflow.
-
E.
PDM
PDM is the station code for Plandome station on the Long Island Rail Road in New York.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e532c15dec8190941e7c7a4cdebb66 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 11:36 a.m.