Triple
T4897327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The words of the Teacher, son of David, king in Jerusalem |
E109712
|
entity |
| Predicate | signalsSetting |
P60522
|
FINISHED |
| Object | ancient Jerusalem |
—
|
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: ancient Jerusalem | Statement: [The words of the Teacher, son of David, king in Jerusalem, signalsSetting, ancient Jerusalem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: signalsSetting Context triple: [The words of the Teacher, son of David, king in Jerusalem, signalsSetting, ancient Jerusalem]
-
A.
featuresSetting
Indicates that something includes, presents, or highlights a particular setting as a notable or primary aspect.
-
B.
setting
Indicates the place, time, or context in which an event, action, or interaction occurs.
-
C.
signalLevel
Indicates the intensity or strength of a transmitted or received signal in a communication context.
-
D.
usesSignaling
Indicates that one entity communicates or coordinates with another by emitting, transmitting, or interpreting signals.
-
E.
stateSetting
Indicates that one entity establishes, configures, or assigns the state or condition of 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd7060f9988190afdf98eb0a38515d |
completed | March 20, 2026, 4:05 p.m. |
Created at: March 20, 2026, 1:28 p.m.