Triple
T25473561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enawené-Nawé |
E638368
|
entity |
| Predicate | territoryProtectionGoal |
P132993
|
FINISHED |
| Object | defense of land rights |
—
|
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: defense of land rights | Statement: [Enawené-Nawé, territoryProtectionGoal, defense of land rights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: territoryProtectionGoal Context triple: [Enawené-Nawé, territoryProtectionGoal, defense of land rights]
-
A.
protectionObjective
Indicates that one entity has the goal or purpose of safeguarding, defending, or preserving another entity or its interests.
-
B.
protectsArea
chosen
Indicates that one entity serves to guard, defend, or preserve a particular area or region from harm or intrusion.
-
C.
aimsToProtect
Indicates an intention or purpose to safeguard or defend one entity, value, or condition from harm, risk, or undesirable outcomes.
-
D.
defenseArea
Indicates a spatial region or zone that is designated for defensive protection or military/security defense activities.
-
E.
protectedGround
Indicates that one entity has taken action to safeguard or defend another entity or area from harm, damage, or unauthorized interference.
- F. None of above.
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_69e75db9b964819096802dcf502e577e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5ffc74fa481909b4fe24a9337f9eb |
completed | May 2, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7f99dc08190afcfb3bc4dfbec1d |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 21, 2026, 2:25 p.m.