Triple
T6961371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saxony |
E161375
|
entity |
| Predicate | troopsAtBattleOfLeipzig |
P73795
|
FINISHED |
| Object | fought initially for Napoleon |
—
|
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: fought initially for Napoleon | Statement: [Saxony, troopsAtBattleOfLeipzig, fought initially for Napoleon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: troopsAtBattleOfLeipzig Context triple: [Saxony, troopsAtBattleOfLeipzig, fought initially for Napoleon]
-
A.
numberOfTroopsInvolved
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
-
B.
numberOfGermanTroopsEncircled
Indicates the quantity of German troops that are surrounded and cut off from escape or reinforcement in a given military situation.
-
C.
opponentInBattleOfLechfeld
Indicates that two entities were opposing sides against each other in the Battle of Lechfeld.
-
D.
PrussianStrengthApprox
Indicates an approximate assessment or estimation of the strength or power associated with Prussia in a given context.
-
E.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
- F. None of above. chosen
Provenance (4 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6daf07e3481909aa79b8e0f1b1be7 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c0b0a08190b262dfc94992994d |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d9bb57e88190a3a7cec34e3b617f |
completed | March 27, 2026, 7:25 p.m. |
Created at: March 27, 2026, 2:30 p.m.