Triple
T202296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Wall |
E4530
|
entity |
| Predicate | visibleLength |
P266
|
FINISHED |
| Object | about 57 meters in the main prayer area |
—
|
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: about 57 meters in the main prayer area | Statement: [Western Wall, visibleLength, about 57 meters in the main prayer area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visibleLength Context triple: [Western Wall, visibleLength, about 57 meters in the main prayer area]
-
A.
length
chosen
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
B.
lengthInWords
Indicates the number of words that make up the length of something, typically a text or expression.
-
C.
width
Indicates the measurement of how wide an entity is, typically the extent of its horizontal dimension from side to side.
-
D.
wordLength
Indicates that there is a relationship specifying the number of characters (length) in a given word.
-
E.
hasApproximateNumberOfLetters
Indicates that an entity is associated with a number that roughly, but not exactly, corresponds to the count of letters it contains.
- 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c2ead8481909996042efcae5e9d |
completed | Feb. 28, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69a25b4a0d448190a6fa6aeb30dc7e13 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:51 a.m.