Triple
T28712329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ebla |
E729861
|
entity |
| Predicate | approximateTabletCount |
P32396
|
FINISHED |
| Object | thousands of cuneiform tablets |
—
|
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: thousands of cuneiform tablets | Statement: [Ebla, approximateTabletCount, thousands of cuneiform tablets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateTabletCount Context triple: [Ebla, approximateTabletCount, thousands of cuneiform tablets]
-
A.
tabletCount
chosen
Indicates the number of tablets associated with or allocated to a given entity or context.
-
B.
occursInTablet
Indicates that an event, statement, or item is recorded or found within a specific tablet.
-
C.
tabletForm
Indicates that something exists or is provided in tablet dosage form.
-
D.
hasNumberOfScreens
Indicates the quantity of screens associated with or contained in a given entity.
-
E.
supportsDeviceCount
Indicates the number of devices that a system, service, or component is capable of supporting concurrently.
- 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_69f043e7d5a4819094b18aca10b1e024 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
Created at: April 28, 2026, 5:48 a.m.