Triple
T3670083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amarna letters |
E77856
|
entity |
| Predicate | numberOfTabletsApproximate |
P32396
|
FINISHED |
| Object | about 380 |
—
|
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 380 | Statement: [Amarna letters, numberOfTabletsApproximate, about 380]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTabletsApproximate Context triple: [Amarna letters, numberOfTabletsApproximate, about 380]
-
A.
tabletCount
chosen
Indicates the number of tablets associated with or allocated to a given entity or context.
-
B.
currentLocationOfMajorTablets
Indicates the present physical location where the major tablets are situated or stored.
-
C.
writingTabletsDate
Indicates that one or more writing tablets are associated with a specific date or time period.
-
D.
writingTabletsContent
Indicates that one or more writing tablets contain or bear a particular written content.
-
E.
writingTabletsSignificance
Indicates the importance or meaningful role that writing tablets have in a given context, situation, or system.
- 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_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc42b3f94819091d51e488bc3f2f2 |
completed | March 8, 2026, 6:47 p.m. |
| PD | Predicate disambiguation | batch_69adb84a20288190a092e4a1b045fe3f |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:25 p.m.