Triple
T29539500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sykes |
E749450
|
entity |
| Predicate | reusesScriptsFrom |
P91997
|
FINISHED |
| Object | Sykes and a... |
—
|
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: Sykes and a... | Statement: [Sykes, reusesScriptsFrom, Sykes and a...]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reusesScriptsFrom Context triple: [Sykes, reusesScriptsFrom, Sykes and a...]
-
A.
usesScriptFor
Indicates that one entity employs or relies on a particular script or writing system for its representation, communication, or operation.
-
B.
laterUsedScript
Indicates that one entity adopted or employed the script of another entity at a later point in time.
-
C.
reusedIn
chosen
Indicates that something previously used in one context or instance is used again in another context or instance.
-
D.
usedInScripts
Indicates that something (such as a tool, method, or resource) is employed or referenced within one or more scripts.
-
E.
usesScriptDerivedFrom
Indicates that one entity employs a writing system that is historically or structurally derived from the script used by another entity.
- 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_69f0bd47abb081909bd6e6a33d770fd8 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66cc9c11c8190b2d06ced137ec777 |
completed | May 2, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f6633ac8a88190ab0cda62bbfcf9b0 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 5:01 p.m.