Triple
T4952789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knob Creek Farm |
E111207
|
entity |
| Predicate | LincolnAgeRangeAtResidence |
P60138
|
FINISHED |
| Object | 2 to 7 years old |
—
|
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: 2 to 7 years old | Statement: [Knob Creek Farm, LincolnAgeRangeAtResidence, 2 to 7 years old]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LincolnAgeRangeAtResidence Context triple: [Knob Creek Farm, LincolnAgeRangeAtResidence, 2 to 7 years old]
-
A.
birthDateOfNotableResident
Indicates the date of birth of a person who is a notable or distinguished resident of a given place.
-
B.
typicalAgeOfVoters
Indicates the usual or most common age range of individuals who participate as voters in elections or voting processes.
-
C.
ageAtEnlistment
Indicates the age a person was when they enlisted in a service, organization, or role.
-
D.
citizenshipDuringLifetime
Indicates that an entity held citizenship in a particular country or political unit at some point during its lifetime.
-
E.
residenceDuringFatherPresidency
Indicates that an entity resided at a particular location during the period when their father was serving as president.
- 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_69bd4418390c8190b7e9766a2512ce55 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71b6a5d481909ad6f5e0b752496c |
completed | March 20, 2026, 4:11 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3aa1388190b3e0c8ee1ba1e4fa |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd6fa2d2088190ae444d3d0e47d5d2 |
completed | March 20, 2026, 4:02 p.m. |
Created at: March 20, 2026, 1:31 p.m.