Triple
T14826549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harden railway station |
E348588
|
entity |
| Predicate | servesTown |
P847
|
FINISHED |
| Object | Harden |
E69894
|
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: Harden | Statement: [Harden railway station, servesTown, Harden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harden Context triple: [Harden railway station, servesTown, Harden]
-
A.
Harden
chosen
Harden is a small rural town in the Riverina region of New South Wales, Australia, known historically as a railway and agricultural service centre.
-
B.
Harden
Harden is a village in West Yorkshire, England, situated near Bingley and known for its residential character and proximity to the countryside.
-
C.
Rodman
Rodman is the given first name of Rod Serling, the influential American screenwriter and creator of "The Twilight Zone."
-
D.
Wilt
Wilt is a satirical comic novel by Tom Sharpe that follows the misadventures of a frustrated polytechnic lecturer entangled in absurd and farcical situations.
-
E.
Wilt
Wilt is a surname most notably associated with Peter Wilt, an American soccer executive known for helping launch and lead several professional soccer clubs in the United States.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded0713700819097bbb0352650984b |
completed | April 14, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe64fab7bc8190af55cc6ec5eafb65 |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 10, 2026, 1:51 a.m.