Triple
T7811148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langho railway station |
E180686
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Langho |
E183275
|
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: Langho | Statement: [Langho railway station, locatedIn, Langho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Langho Context triple: [Langho railway station, locatedIn, Langho]
-
A.
Langho
chosen
Langho is a village in Lancashire, England, situated within the rural borough of Ribble Valley.
-
B.
Longu
Longu is an Austronesian language spoken in the Solomon Islands, known primarily as a local name for the Longgu language.
-
C.
Changling
Changling is the largest and best-preserved mausoleum within Beijing’s Ming Tombs complex, built for the Yongle Emperor and his empress.
-
D.
Longleng
Longleng is a town and administrative center in the northeastern Indian state of Nagaland, known as the headquarters of Longleng district.
-
E.
Helong
Helong is a county-level city in northeastern China's Jilin Province, known for its significant ethnic Korean population and role within the Yanbian Korean Autonomous Prefecture.
- 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_69ca827f6f148190beca4e245b993506 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78cd1cc8190b4cdd9850e1e2bb7 |
completed | March 30, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbdecc6c5c8190af4445928ce1132f |
completed | March 31, 2026, 2:48 p.m. |
Created at: March 30, 2026, 4:37 p.m.