Triple
T1219459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Amphitheatre of Alexandria |
E26184
|
entity |
| Predicate | numberOfSeatingRows |
P25953
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [Roman Amphitheatre of Alexandria, numberOfSeatingRows, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSeatingRows Context triple: [Roman Amphitheatre of Alexandria, numberOfSeatingRows, 13]
-
A.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
B.
numberOfSittings
Indicates the total count of distinct sittings or sessions associated with an entity or event.
-
C.
seatingConfiguration
Indicates how seats are arranged or organized relative to each other in a given context.
-
D.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
E.
ridersPerRow
Indicates the number of riders assigned or allowed to sit in each row.
- 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_69a4948331fc8190b531ac9bec71c491 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be1d55a08190a138b2411a7c4376 |
completed | March 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69a4bb644af08190ba25905f20adb01a |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd3140688190ac6e24de157fd61e |
completed | March 1, 2026, 10:26 p.m. |
Created at: March 1, 2026, 7:46 p.m.