Triple
T1416022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Admiralty Arch |
E31918
|
entity |
| Predicate | wasLeasedFor |
P27529
|
FINISHED |
| Object | hotel development |
—
|
LITERAL 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: hotel development | Statement: [Admiralty Arch, wasLeasedFor, hotel development]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasLeasedFor Context triple: [Admiralty Arch, wasLeasedFor, hotel development]
-
A.
leasedFrom
Indicates that one entity is renting or leasing something from another entity, which acts as the owner or lessor.
-
B.
inUseSince
Indicates that an entity has been actively in use starting from a specified point in time.
-
C.
usedEquipmentFrom
Indicates that one entity has utilized or operated equipment that originated from or was provided by another entity.
-
D.
ownedDuring
Indicates that one entity possessed or held ownership of another entity for some or all of a specified time interval.
-
E.
occupationDuration
Indicates the length of time an entity holds or has held a particular occupation or role.
- F. None of above. chosen
Provenance (4 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c402b1648190b87802d9beb2712e |
completed | March 1, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69a4bf060b0081909ba00e6ac093a28b |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c06721488190ac7f6e012f21af3d |
completed | March 1, 2026, 10:40 p.m. |
Created at: March 1, 2026, 7:59 p.m.