Triple
T59174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gombe Stream Research Centre |
E1171
|
entity |
| Predicate | dataTypeCollected |
P4241
|
FINISHED |
| Object | long-term behavioral observations |
—
|
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: long-term behavioral observations | Statement: [Gombe Stream Research Centre, dataTypeCollected, long-term behavioral observations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataTypeCollected Context triple: [Gombe Stream Research Centre, dataTypeCollected, long-term behavioral observations]
-
A.
dataModel
Indicates a relationship where an entity defines, uses, or is structured according to a specific data model or schema.
-
B.
dataUse
Indicates how data is intended to be accessed, processed, or applied within a particular context or activity.
-
C.
resultType
Indicates the type or category of outcome that is produced by a given process, action, or operation.
-
D.
demographicCharacteristic
Indicates that one entity specifies or describes a demographic attribute or feature (such as age, gender, ethnicity, or similar population-related trait) of another entity.
-
E.
demographicsCharacteristic
Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another 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_69a24a552ef88190a0df287d68c65cba |
completed | Feb. 28, 2026, 1:52 a.m. |
| NER | Named-entity recognition | batch_69a250e401288190ba12322c9c5f07c9 |
completed | Feb. 28, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69a24e9f40908190a2f4a2111469b733 |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a250e2a80881909e5a653260e6f8e0 |
completed | Feb. 28, 2026, 2:20 a.m. |
Created at: Feb. 28, 2026, 1:55 a.m.