Triple
T36001879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baab ar-Rayyan |
E1041153
|
entity |
| Predicate | numberOfGatesContext |
P207129
|
FINISHED |
| Object | one of the gates of Paradise |
—
|
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: one of the gates of Paradise | Statement: [Baab ar-Rayyan, numberOfGatesContext, one of the gates of Paradise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGatesContext Context triple: [Baab ar-Rayyan, numberOfGatesContext, one of the gates of Paradise]
-
A.
numberOfGates
Indicates the quantity of gates associated with or belonging to an entity.
-
B.
lengthOfEachGate
Indicates the measurement of the individual length associated with each gate in a set or system.
-
C.
hasBoardingGatesFor
Indicates that a location or facility provides designated boarding gates used for embarking passengers onto specific transportation services (such as flights or trains).
-
D.
numberOfGatehouses
Indicates the quantity of gatehouses associated with or present at a given entity or location.
-
E.
hasPassengerBoardingGates
Indicates that an entity is associated with or contains one or more passenger boarding gates used for embarking or disembarking passengers.
- 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_69f76e2a02208190aedd1f9025a8b300 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:07 p.m.