Triple
T645160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hayes, Kent, England |
E11224
|
entity |
| Predicate | directionFromCharingCross |
P16893
|
FINISHED |
| Object | south-east |
—
|
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: south-east | Statement: [Hayes, Kent, England, directionFromCharingCross, south-east]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: directionFromCharingCross Context triple: [Hayes, Kent, England, directionFromCharingCross, south-east]
-
A.
locationDuring_Operation Crossroads
Indicates that an entity was located at a particular place during the time period of Operation Crossroads.
-
B.
builtAcrossStreetFrom
Indicates that one structure was constructed on the opposite side of a street directly facing another structure.
-
C.
crossingType
Indicates the specific kind or category of crossing (e.g., how or where one thing passes over, through, or across another).
-
D.
hasApproachRoad
Indicates that one entity is connected to or accessed by another entity via an approach road leading to it.
-
E.
hasTrafficDirection
Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f19f9a08190b0bf6e19b32427ff |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0a0ab481909871461418a00be7 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49dc0e6a08190b81d82a6f2571c41 |
completed | March 1, 2026, 8:12 p.m. |
Created at: March 1, 2026, 7:36 p.m.