Triple
T11194028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greenfield railway station |
E264874
|
entity |
| Predicate | stationCode |
P1289
|
FINISHED |
| Object | GNF |
E772779
|
NE 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: GNF | Statement: [Greenfield railway station, stationCode, GNF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GNF Context triple: [Greenfield railway station, stationCode, GNF]
-
A.
GNF
chosen
GNF is the official currency code for the Guinean franc, the national currency of Guinea.
-
B.
GN
GN is a fast, meta-build system tool used primarily by the Chromium project to generate build files for Ninja.
-
C.
FGN
FGN is the acronym commonly used to refer to the federal-level governing authority of the Federal Republic of Nigeria.
-
D.
GF
GF is the vehicle registration code used on license plates for the district of Gifhorn in Lower Saxony, Germany.
-
E.
GF
GF is the vehicle registration code assigned to the district that includes the Austrian town of Deutsch-Wagram.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8bf14e481908563b15790af4d20 |
completed | April 9, 2026, 5:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e483f8ecf4819086f0bab3ca9ddcb4 |
completed | April 19, 2026, 7:27 a.m. |
Created at: April 8, 2026, 9:29 p.m.