Triple
T278881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | War Office |
E5309
|
entity |
| Predicate | headquartersLocation |
P62
|
FINISHED |
| Object | Whitehall |
E16070
|
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: Whitehall | Statement: [War Office, headquartersLocation, Whitehall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Whitehall Context triple: [War Office, headquartersLocation, Whitehall]
-
A.
Whitehall
chosen
Whitehall is the central London district that serves as the administrative heart of the United Kingdom, housing many key government departments and ministries.
-
B.
Whitehall Terminal
Whitehall Terminal is the Manhattan ferry terminal that serves as the primary departure and arrival point for the Staten Island Ferry across New York Harbor.
-
C.
Hyde Park
Hyde Park is a historic town in New York’s Hudson Valley best known as the longtime home of President Franklin D. Roosevelt and several notable Gilded Age estates.
-
D.
Hyde Park
"Hyde Park" is a Caroline-era comedy play by James Shirley, known for its witty depiction of London society and romantic intrigues set around the famous London park.
-
E.
Hyde Park
Hyde Park is a historic and upscale residential and shopping district located just southwest of downtown Tampa, Florida.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25def95c48190bb8ab2259f67b583 |
completed | Feb. 28, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3a336d8b08190988eaf39f950f8cd |
completed | March 1, 2026, 2:23 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.