Triple
T641751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diccionario histórico de la lengua española |
E16753
|
entity |
| Predicate | publisher |
P29
|
FINISHED |
| Object | RAE |
E13985
|
NE 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: RAE | Statement: [Diccionario histórico de la lengua española, publisher, RAE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RAE Context triple: [Diccionario histórico de la lengua española, publisher, RAE]
-
A.
RAE
chosen
RAE is the commonly used acronym for the Royal Spanish Academy, the official institution responsible for regulating and overseeing the Spanish language.
-
B.
RALE
RALE is the station code for Alewife, the northern terminus of Boston’s MBTA Red Line rapid transit service.
-
C.
RA
RA is the commonly used abbreviation for the Royal Regiment of Artillery, a principal artillery branch of the British Army.
-
D.
AAR
AAR is the American Association of Railroads' wheel arrangement classification system commonly used to describe locomotive axle configurations in North America.
-
E.
RAN
RAN is the 3GPP working group responsible for specifying the radio access network technologies used in mobile communication systems such as LTE and 5G.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49f02bc2c8190b8a92b2505768c19 |
completed | March 1, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5778faa788190ac246d6cd6b983f4 |
completed | March 2, 2026, 11:42 a.m. |
Created at: March 1, 2026, 7:36 p.m.