Triple
T26742007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shoshenq II |
E674286
|
entity |
| Predicate | scriptUsedOnMonuments |
P159127
|
FINISHED |
| Object | Egyptian hieroglyphs |
—
|
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: Egyptian hieroglyphs | Statement: [Shoshenq II, scriptUsedOnMonuments, Egyptian hieroglyphs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptUsedOnMonuments Context triple: [Shoshenq II, scriptUsedOnMonuments, Egyptian hieroglyphs]
-
A.
scriptUsedInMonuments
chosen
Indicates that a particular writing system or script is employed in the inscriptions or textual elements found on specific monuments.
-
B.
appliesToMonument
Indicates that something (such as a rule, status, or attribute) is relevant or applicable specifically to a monument.
-
C.
usedInMonument
Indicates that something serves as a material, component, or element incorporated into the construction or design of a monument.
-
D.
resultForMonument
Indicates that something (such as data, analysis, or an outcome) is the result specifically associated with a given monument.
-
E.
hasScheduledMonument
Indicates that an entity is associated with, or contains, a site or structure officially designated as a scheduled monument.
- 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_69eecda63a3881908095c47900692e65 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f64dbbaefc8190952b8320bf4397d8 |
completed | May 2, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 3:49 a.m.