Triple
T27839319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Procnias tricarunculatus |
E703635
|
entity |
| Predicate | wattleCount |
P163401
|
FINISHED |
| Object | three facial wattles on male |
—
|
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: three facial wattles on male | Statement: [Procnias tricarunculatus, wattleCount, three facial wattles on male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wattleCount Context triple: [Procnias tricarunculatus, wattleCount, three facial wattles on male]
-
A.
hasWattles
Indicates that an entity possesses wattles, which are fleshy, often hanging skin structures typically found on the head or neck.
-
B.
wattlesColor
Indicates the color or coloration pattern of an entity's wattles.
-
C.
numberOfTrees
Indicates the count or quantity of trees associated with a given entity or context.
-
D.
numberOfWires
Indicates the quantity of wires associated with or contained in a given entity.
-
E.
hasNumberOfWuku
Indicates the relationship that specifies how many wuku (traditional Javanese calendar weeks) are associated with a given entity.
- 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_69ef840d9e3c819093615ebff4ec22be |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f638d3a96c81908600129b3f4d941a |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f6318ae6f08190b3f85f9201046a15 |
completed | May 2, 2026, 5:16 p.m. |
| PDg | Predicate description generation | batch_69f6359d46b88190922dd7de508e3b0e |
completed | May 2, 2026, 5:34 p.m. |
Created at: April 27, 2026, 6:01 p.m.