Triple
T17740551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tel Zayit |
E442841
|
entity |
| Predicate | typeOfWritingFound |
P93281
|
FINISHED |
| Object | alphabetic inscription |
—
|
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: alphabetic inscription | Statement: [Tel Zayit, typeOfWritingFound, alphabetic inscription]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfWritingFound Context triple: [Tel Zayit, typeOfWritingFound, alphabetic inscription]
-
A.
fieldOfWriting
Indicates that one entity is the domain, genre, or subject area in which another entity writes or produces written work.
-
B.
writTypes
Indicates the types or categories of writs (formal written legal orders) associated with an action or entity.
-
C.
hasWritingType
chosen
Indicates that one entity is associated with, or characterized by, a particular type or form of writing.
-
D.
mannerOfWriting
Indicates the way or style in which something is written or expressed in writing.
-
E.
literatureType
Indicates the specific category or genre of literature that characterizes or classifies a given work or text.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47acc2610819099451b02bb51891f |
completed | April 19, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69e3cde815e08190881972e2d80d151e |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:09 a.m.