Triple
T18902940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Deadly Education |
E462380
|
entity |
| Predicate | protagonistAlias |
P19776
|
FINISHED |
| Object | El |
—
|
NE NERFINISHED |
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: El | Statement: [A Deadly Education, protagonistAlias, El]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: El Context triple: [A Deadly Education, protagonistAlias, El]
-
A.
El
El is the chief god of the ancient Canaanite pantheon, often depicted as a patriarchal creator and father of other deities.
-
B.
El
El is the given name of El Anatsui, the renowned Ghanaian-Nigerian sculptor celebrated for his monumental metal wall hangings made from recycled materials.
-
C.
El
El is the common nickname for Philadelphia’s elevated Market–Frankford rapid transit line operated by SEPTA.
-
D.
El
chosen
El, short for Galadriel Higgins, is the sharp-tongued, powerfully gifted dark sorceress who serves as the central protagonist of Naomi Novik’s Scholomance trilogy.
-
E.
Le
Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c52a4b4c8190b5821996e3c1741d |
completed | April 20, 2026, 6:18 a.m. |
Created at: April 10, 2026, 11:58 a.m.