Triple
T24510454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Private Investment in India 1900–1939 |
E606200
|
entity |
| Predicate | timePeriodAnalyzedStart |
P156559
|
FINISHED |
| Object | 1900 |
—
|
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: 1900 | Statement: [Private Investment in India 1900–1939, timePeriodAnalyzedStart, 1900]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodAnalyzedStart Context triple: [Private Investment in India 1900–1939, timePeriodAnalyzedStart, 1900]
-
A.
timePeriodAnalyzed
Indicates that a specified time period is the focus or scope of an analysis or evaluation.
-
B.
recordedInPeriodStart
Indicates that an event or record began or was first documented at the start of a specified time period.
-
C.
timePeriodOrigin
Indicates that one entity is the time period in which the other entity originated or first came into existence.
-
D.
usePeriodStart
Indicates that an entity begins to be used or becomes active starting from a specified time period.
-
E.
startDate
Indicates the point in time when an event, state, or relationship begins.
- 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_69e2c4c725148190a4e41577c5cb409c |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a9d912e88190bc39c05a9d7f407e |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6a4580481908fddc385f5262f95 |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2a9d795288190916368e3cec1f666 |
completed | April 30, 2026, 1:01 a.m. |
Created at: April 18, 2026, 2:23 a.m.