Triple
T28626805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maşat Höyük |
E724546
|
entity |
| Predicate | tabletsContain |
P33759
|
FINISHED |
| Object | administrative texts |
—
|
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: administrative texts | Statement: [Maşat Höyük, tabletsContain, administrative texts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tabletsContain Context triple: [Maşat Höyük, tabletsContain, administrative texts]
-
A.
tabletCount
Indicates the number of tablets associated with or allocated to a given entity or context.
-
B.
tabletsLanguage
Indicates that the language used on or in the tablets is a particular specified language.
-
C.
writingTabletsContent
chosen
Indicates that one or more writing tablets contain or bear a particular written content.
-
D.
tabletContentDivision
Indicates how the content displayed on a tablet device is partitioned or divided into distinct sections or regions.
-
E.
currentLocationOfMajorTablets
Indicates the present physical location where the major tablets are situated or stored.
- 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_69f01d822ac08190932de59ec2268ed2 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c2198208190a3954086c22cfcbf |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 4:36 a.m.