Triple
T2055296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red-tailed hawk |
E45659
|
entity |
| Predicate | monogamy |
P35624
|
FINISHED |
| Object | often forms long-term pair bonds |
—
|
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: often forms long-term pair bonds | Statement: [Red-tailed hawk, monogamy, often forms long-term pair bonds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: monogamy Context triple: [Red-tailed hawk, monogamy, often forms long-term pair bonds]
-
A.
monogeneric
Indicates that a taxonomic group (such as a family or subfamily) contains only a single genus.
-
B.
marriageType
Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
-
C.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
D.
marries
Indicates that one entity enters into a legally or socially recognized marital union with another entity.
-
E.
neverMarried
Indicates that the subject has not been legally married to any partner at any time up to the present.
- 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_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9a9ce548190a5a3488fafb2e79e |
completed | March 7, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_69abb7abba508190b872f345d3ba51bb |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb94ec400819097596732aabed854 |
completed | March 7, 2026, 5:36 a.m. |
Created at: March 4, 2026, 7:40 p.m.