Triple
T34188403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koderma district |
E877025
|
entity |
| Predicate | literacyCharacteristic |
P111042
|
FINISHED |
| Object | developing literacy rate |
—
|
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: developing literacy rate | Statement: [Koderma district, literacyCharacteristic, developing literacy rate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literacyCharacteristic Context triple: [Koderma district, literacyCharacteristic, developing literacy rate]
-
A.
typeOfLiteracy
Indicates the specific kind or category of literacy (e.g., digital, financial, media) that characterizes an entity’s literacy skills or practices.
-
B.
literacyStatus
Indicates whether an entity possesses the ability to read and write, or its level of literacy.
-
C.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
D.
bookCharacteristic
Indicates that a particular characteristic, feature, or attribute is associated with a given book.
-
E.
hasLiteracyConcern
chosen
Indicates that an entity has an identified issue, risk, or challenge related to literacy skills or abilities.
- F. None of above.
Provenance (3 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_69f349af20a4819089ac24d28f2d8112 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 1, 2026, 1:55 a.m.