Triple
T14894494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hook railway station |
E359835
|
entity |
| Predicate | stationCode |
P1289
|
FINISHED |
| Object | HOK |
E27535
|
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: HOK | Statement: [Hook railway station, stationCode, HOK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HOK Context triple: [Hook railway station, stationCode, HOK]
-
A.
HOK Group
chosen
HOK Group is a global design, architecture, engineering, and planning firm known for large-scale commercial, civic, and sports projects.
-
B.
HKS
HKS is the Harvard Kennedy School, a leading public policy and public administration graduate school at Harvard University.
-
C.
HKS, Inc.
HKS, Inc. is a global architecture firm known for designing major sports, entertainment, and commercial venues.
-
D.
HKS Architects
HKS Architects is a global architecture firm known for designing large-scale commercial, mixed-use, and hospitality projects.
-
E.
Perkins+Will
Perkins+Will is a global architecture and design firm known for its innovative, sustainable projects across sectors such as education, healthcare, and cultural institutions.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded5f9d10c819091732d7a5a42a682 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b679fb081908cf8f41acfba3b99 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 10, 2026, 2:10 a.m.