Triple
T16888855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2nd Guards Tank Army |
E421610
|
entity |
| Predicate | hasHonorificTitle |
P368
|
FINISHED |
| Object | Guards |
E171617
|
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: Guards | Statement: [2nd Guards Tank Army, hasHonorificTitle, Guards]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guards Context triple: [2nd Guards Tank Army, hasHonorificTitle, Guards]
-
A.
Guards
chosen
Guards is an honorific military designation historically awarded to elite, highly distinguished units in various armed forces, particularly in the Soviet and Russian militaries.
-
B.
A Guarda
A Guarda is a coastal town in northwestern Spain known for its fishing heritage and the nearby ancient Celtic hillfort of Santa Trega.
-
C.
La Guardia
La Guardia is an Italian-origin surname most famously associated with Fiorello H. La Guardia, the influential three-term mayor of New York City in the early 20th century.
-
D.
The Guard
The Guard is a character portrayed by Frank Morgan, best remembered as the bumbling yet endearing gatekeeper at the Emerald City in the classic film "The Wizard of Oz."
-
E.
The Guard
The Guard is a darkly comedic Irish crime film in which Brendan Gleeson plays an unconventional small-town police officer drawn into an international drug-smuggling investigation.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3bbc2f6d081909c76fa2a6b87e083 |
completed | April 18, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c2befaa88190ba83dc17aa66b541 |
completed | May 10, 2026, 5:39 p.m. |
Created at: April 10, 2026, 5:29 a.m.