Triple
T869329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aztec Empire |
E18773
|
entity |
| Predicate | tributeSystem |
P20381
|
FINISHED |
| Object | regional tribute provinces |
—
|
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: regional tribute provinces | Statement: [Aztec Empire, tributeSystem, regional tribute provinces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tributeSystem Context triple: [Aztec Empire, tributeSystem, regional tribute provinces]
-
A.
tributeMethod
Indicates the means or manner by which tribute is given, delivered, or fulfilled between parties.
-
B.
tributeTo
Indicates that one entity is created, given, or dedicated as a mark of respect, admiration, or honor toward another entity.
-
C.
contributeTo
Indicates that one entity provides support, resources, or effort that helps bring about, enhance, or maintain another entity, outcome, or state.
-
D.
donated
Indicates that one entity voluntarily gave something of value (such as money, goods, or time) to another entity, typically without expecting anything in return.
-
E.
creditedFor
Indicates that one entity is acknowledged as the source, contributor, or originator responsible for another entity (such as a work, achievement, or outcome).
- 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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac811e548190a72b7a10b5ea8665 |
completed | March 1, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69a4aa89ca008190b50d061ac7fe19f9 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab498bb0819080e3afb684b504b6 |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:39 p.m.