Triple
T30819175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Safā and Marwah area |
E784868
|
entity |
| Predicate | greenLightMarkersIndicate |
P8566
|
FINISHED |
| Object | area of brisk walking for men |
—
|
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: area of brisk walking for men | Statement: [Safā and Marwah area, greenLightMarkersIndicate, area of brisk walking for men]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: greenLightMarkersIndicate Context triple: [Safā and Marwah area, greenLightMarkersIndicate, area of brisk walking for men]
-
A.
roadSignColor
Indicates the color attribute associated with a particular road sign.
-
B.
lightingOfLampsSignifies
Indicates that the act of lighting lamps serves as a sign, symbol, or marker of a particular event, state, or significance.
-
C.
roadSignageIndicates
chosen
Indicates that a piece of road signage conveys, displays, or communicates specific information, instructions, or warnings about road conditions or regulations.
-
D.
lighthouseColor
Indicates the color attribute associated with a lighthouse.
-
E.
hasTrafficSignals
Indicates that traffic control signals are present at or associated with a given location or roadway feature.
- F. None of above.
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_69f224b4eda48190bd212ce4f3901e56 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6906b8f048190b3051f9ece75bd3a |
completed | May 3, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:44 p.m.